{"id":2405,"date":"2025-05-05T13:31:58","date_gmt":"2025-05-05T17:31:58","guid":{"rendered":"https:\/\/www.bu.edu\/online\/?post_type=bu-program-page&#038;p=2405"},"modified":"2026-02-27T13:35:24","modified_gmt":"2026-02-27T18:35:24","slug":"ms-applied-data-analytics","status":"publish","type":"bu-program-page","link":"https:\/\/www.bu.edu\/online\/degrees-certificates\/analytics-data-business-programs\/ms-applied-data-analytics\/","title":{"rendered":"Online Master of Science in Applied Data Analytics"},"content":{"rendered":"\n<h2><strong>Develop In-Demand Data Analytics Skills<\/strong><\/h2>\n\n\n\n<p>With data analytics needs influencing every major industry\u2014including health care, tech, finance, communication, entertainment, energy, transportation, government, and manufacturing, to name some\u2014there is significant growth in specialized data science and machine learning areas. The demand for skilled talent continues to outpace supply, with McKinsey Global Institute anticipating a shortfall of up to 250,000 data scientists through the decade.&nbsp;<\/p>\n\n\n\n<p>The Master of Science in Applied Data Analytics (MSADA) program provides solid knowledge of data analytics and examines the presentation and applications of the latest industry tools and approaches within an academically rigorous framework. Emphasizing both data analytics and applied areas\u2014including databases, applied machine learning, and large dataset processing methods\u2014the MSADA curriculum provides a thorough immersion in concepts and techniques for organizing, cleaning, analyzing, and representing\/visualizing large amounts of data. Students will be exposed to various database systems, data mining tools, data visualization tools and packages, Python packages, R packages, and cloud services. The knowledge of analytics tools combined with an understanding of data mining and machine learning approaches will enable students to critically analyze real-world problems and understand the possibilities and limitations of analytics applications.&nbsp;<\/p>\n\n\n\n<p>There are two optional concentrations to choose from:<\/p>\n\n\n\n<ul><li><a href=\"https:\/\/www.bu.edu\/online\/degrees-certificates\/analytics-data-business-programs\/ms-applied-data-analytics-ai-machine-learning\/\">AI &amp; Machine Learning<\/a><\/li><li><a href=\"https:\/\/www.bu.edu\/online\/degrees-certificates\/analytics-data-business-programs\/ms-applied-data-analytics-data-engineering\/\">Data Engineering<\/a><\/li><\/ul>\n\n\n\n<p>The MS in Applied Data Analytics is also available on campus in Boston.&nbsp;<a href=\"https:\/\/www.bu.edu\/met\/degrees-certificates\/ms-applied-data-analytics\/\" target=\"_blank\" rel=\"noreferrer noopener\">Learn more<\/a>.<\/p>\n\n\n\n<h2>Curriculum<\/h2>\n\n\n\n<p>A total of ten courses (40 units) is required. Students exempted from the foundation courses will complete a total of eight courses (32 units).<\/p>\n\n\n\n<p>Students not choosing a concentration must complete recommended prerequisites along with the foundation courses, core courses, and general electives. Students pursuing a concentration should review the requirements for&nbsp;<a href=\"https:\/\/www.bu.edu\/met\/degrees-certificates\/ms-applied-data-analytics-ai-machine-learning\/\" target=\"_blank\" rel=\"noreferrer noopener\">AI &amp; Machine Learning<\/a>&nbsp;or&nbsp;<a href=\"https:\/\/www.bu.edu\/met\/degrees-certificates\/ms-applied-data-analytics-data-engineering\/\" target=\"_blank\" rel=\"noreferrer noopener\">Data Engineering<\/a>.<\/p>\n\n\n<div class=\"bu_collapsible_container \" aria-live=\"polite\" data-customize-animation=\"false\"><h3 class=\"bu_collapsible\" aria-expanded=\"false\"tabindex=\"0\" role=\"button\">Prerequisites<\/h3><div class=\"bu_collapsible_section\" style=\"display: none;\"><\/p>\n\n\n\n<p>Applicants to the program are required to have a bachelor\u2019s degree in any discipline from a regionally accredited institution. Students with limited academic background in information technology, computer science, and mathematics may be required to enroll in one or more of the following complimentary labs. Recommendations will be provided upon admission.<\/p>\n\n\n\n<p>Prerequisites (open to all students):<\/p>\n\n\n\n<ul><li>MET LB 103 Core Mathematical Concepts<\/li><li>MET LB 104 Foundations of Probability<\/li><li>MET LB 115 Database Fundamentals<\/li><\/ul>\n\n\n<p><\/div>\n<\/div>\n\n\n\n<div class=\"bu_collapsible_container \" aria-live=\"polite\" data-customize-animation=\"false\"><h3 class=\"bu_collapsible\" aria-expanded=\"false\"tabindex=\"0\" role=\"button\">Foundation Courses<\/h3><div class=\"bu_collapsible_section\" style=\"display: none;\"><\/p>\n\n\n\n<p>(Two courses\/8 units)<\/p>\n\n\n\n<p>Qualified students may be exempt from one or both foundation courses based on previous academic background in information technology, computer science, and mathematics. Applicants will be notified of their curriculum requirements upon admission. If foundation courses are assigned, they must be completed within the first semester of study.<\/p>\n\n\n<p><div class=\"course-feed\"><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">521<\/span><\/span> Information Structures with Python<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        <div class=\"cf-hub-ind\">  <a href=\"http:\/\/www.bu.edu\/hub\/what-is-the-hub\/\" target=\"_blank\" class=\"cf-hub-head\" alt=\"BU Hub\">    <span aria-hidden=\"true\" class=\"bu-hub-iconstyles icon-buhub\">BU Hub<\/span>  <\/a>  <a href=\"http:\/\/www.bu.edu\/hub\/what-is-the-hub\/\" target=\"_blank\" class=\"hub-head\">    <span aria-hidden=\"true\" class=\"bu-hub-iconstyles icon-questionmark\">Learn More<\/span>  <\/a>  <ul class=\"cf-hub-offerings\"><li class=\"cf-hub-area-4\">Creativity\/Innovation<\/li><li class=\"cf-hub-area-1\">Critical Thinking<\/li><li class=\"cf-hub-area-H\">Quantitative Reasoning II<\/li>  <\/ul><\/div>\n\t\t<p class=\"cf-course-description\">This course covers the concepts of the object-oriented approach to software design and development using Python. It includes a detailed discussion of programming concepts starting with the fundamentals of data types, control structures methods, classes, arrays and strings, and proceeding to advanced topics such as inheritance and polymorphism, creating user interfaces, exceptions and streams. Upon completion of this course students will be able to apply software engineering principles to design and implement Python applications that can be used in with analytics and big data. Effective Fall 2021, this course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Creativity\/Innovation, Critical Thinking. Prerequisite: Programming experience in any language. Or Instructor's consent.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Mohan<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">T<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=MET\">MET 122<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O1, SPRG 2026 <span class=\"cf-section-dates\">Jan 13th to Mar 2nd<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Zhang<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O2, SPRG 2026 <span class=\"cf-section-dates\">Mar 10th to Apr 27th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Trajanov<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">526<\/span><\/span> Data Structures and Algorithms<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS300 and either MET CS520 or MET CS521, or consent of instructor. This course covers and relates fundamental components of programs. Students use various data structures to solve computational problems, and implement data structures using a high-level programming language. Algorithms are created, decomposed, and expressed as pseudocode. The running time of various algorithms and their computational complexity are analyzed.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O1, SPRG 2026 <span class=\"cf-section-dates\">Jan 13th to Mar 2nd<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Braude<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O2, SPRG 2026 <span class=\"cf-section-dates\">Mar 10th to Apr 27th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Zhang<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><\/div><\/p>\n\n\n<p><\/div>\n<\/div>\n\n\n\n<div class=\"bu_collapsible_container \" aria-live=\"polite\" data-customize-animation=\"false\"><h3 class=\"bu_collapsible\" aria-expanded=\"false\"tabindex=\"0\" role=\"button\">Core Courses<\/h3><div class=\"bu_collapsible_section\" style=\"display: none;\"><\/p>\n\n\n\n<p>(Four courses \/ 16 credits)<\/p>\n\n\n<p><div class=\"course-feed\"><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">555<\/span><\/span> Foundations of Machine Learning<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 544 or MET CS 550 or consent of instructor.  Learn the foundations of machine learning, regression, and classification. Topics include how to describe data, statistical inference, 1 and 2 sample tests of means and proportions, simple linear regression, multiple linear regression, multinomial regression, logistic regression, analysis of variance, and regression diagnostics. These topics are explored using the statistical package R, with a focus on understanding how to use these methods and interpret their outputs and how to visualize the results. In each topic area, the methodology, including underlying assumptions and the mechanics of how it all works along with appropriate interpretation of the results are discussed. Concepts are presented in context of real-world examples in order to help you learn when and how to deploy different methods.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Zhang<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">R<\/td>\n\t<td class=\"cf-section-start\">12:30:00 PM&ndash;03:15:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=COM\">COM 217<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A2, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Alizadeh-Shabdiz<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">W<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=CAS\">CAS 116<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O2, SPRG 2026 <span class=\"cf-section-dates\">Mar 10th to Apr 27th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Alizadeh-Shabdiz<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">577<\/span><\/span> Data Science with Python<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\"><\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisite: (MET CS 521) or equivalent or instructor's consent. Students will learn major Python tools and techniques for data analysis. There are weekly assignments and mini projects on topics covered in class. These assignments will help build necessary statistical, visualization and other data science skills for effective use of data science in a variety of applications including finance, text processing, time series analysis and recommendation systems. In addition, students will choose a topic for a final project and present it on the last day of class.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Pinsky<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">W<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=CAS\">CAS 313<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A2, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Pinsky<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">T<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=HAR\">HAR 210<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O2, SPRG 2026 <span class=\"cf-section-dates\">Mar 10th to Apr 27th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Mohan<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><\/div><\/p>\n\n\n\n<div style=\"border-top: 1px solid #ddd;\"><p style=\"font-weight: bold; font-style: italic; font-size:105%;margin-top:20px;\">Plus one course from the following:<\/p><\/div>\n\n\n<p><div class=\"course-feed\"><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">544<\/span><\/span> Foundations of Analytics and Data Visualization<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET LB 103, MET LB 104, and (METCS 520 or METCS 521), or equivalent knowledge, or consent of instructor. The goal of this course is to provide students with the mathematical and practical background required in the field of data analytics. Probability and statistics concepts will be reviewed as well as the R tool for statistical computing and graphics. Different types of data are investigated along with data summarization techniques and plotting methods. Data populations using discrete, continuous, and multivariate distributions are explored. Sampling methods and errors during measurements and computations are analyzed in the course. String manipulations and data wrangling methods are examined in detail. The concepts covered in the course are demonstrated using R. Laboratory Course. Restrictions: This course may not be taken in conjunction with MET CS 550.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Rizinski<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">M<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=MET\">MET 122<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O1, SPRG 2026 <span class=\"cf-section-dates\">Jan 13th to Mar 2nd<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Kalathur<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">550<\/span><\/span> Computational Mathematics for Machine Learning<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: Basic knowledge of Python or R; or consent of instructor. - Mathematics is fundamental to data science and machine learning. In this course, you will review essential mathematical concepts and fundamental procedures illustrated by Python and\/or R code and visualizations. Computational methods for data science presented through accessible, self-contained examples, intuitive explanations, and visualization will be discussed. Equal emphasis will be placed on both mathematics and computational methods that are at the heart of many algorithms for data analysis and machine learning. You will also advance your mathematical proficiency, enabling you to effectively apply your skills to data analytics and machine learning. Restrictions: This course may not be taken in conjunction with MET CS 544.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Pinsky<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">M<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=SOC\">SOC B57<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O1, SPRG 2026 <span class=\"cf-section-dates\">Jan 13th to Mar 2nd<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Pinsky<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><\/div><\/p>\n\n\n\n<div style=\"border-top: 1px solid #ddd;\"><p style=\"font-weight: bold; font-style: italic; font-size:105%;margin-top:20px;\">And one course from the following*:<\/p><\/div>\n\n\n<p><div class=\"course-feed\"><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">688<\/span><\/span> Web Mining and Graph Analytics<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 544, or MET CS 555 or equivalent knowledge, or instructor's consent. - The Web Mining and Graph Analytics course covers the areas of web mining, machine learning fundamentals, text mining, clustering, and graph analytics. This includes learning fundamentals of machine learning algorithms, how to evaluate algorithm performance, feature engineering, content extraction, sentiment analysis, distance metrics, fundamentals of clustering algorithms, how to evaluate clustering performance, and fundamentals of graph analysis algorithms, link analysis and community detection based on graphs. Laboratory Course.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Hajiyani<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">M<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=FLR\">FLR 123<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O2, SPRG 2026 <span class=\"cf-section-dates\">Mar 10th to Apr 27th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Rawassizadeh<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">699<\/span><\/span> Data Mining<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 521, MET LB 103 and MET LB 104; and either MET CS 579 or MET CS 669;  or consent of instructor. - Study basic concepts and techniques of data mining. Topics include data preparation, classification, performance evaluation, association rule mining, regression and clustering. You will learn underlying theories of data mining algorithms in the class and practice those algorithms through assignments and a semester-long class project using R. After finishing this course, you will be able to independently perform data mining tasks to solve real-world problems.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A2, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Lee<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">W<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=MCS\">MCS B33<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O1, SPRG 2026 <span class=\"cf-section-dates\">Jan 13th to Mar 2nd<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Lee<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><\/div><\/p>\n\n\n\n<div style=\"border-top: 1px solid #ddd;\"><p style=\"font-weight: bold; font-style: italic; font-size:105%;margin-top:20px;\">*If choosing to take both MET CS 688 and MET CS 699, one will be counted as a core course and the other as a general elective.<\/p><\/div>\n\n\n<p><\/div>\n<\/div>\n\n\n\n<div class=\"bu_collapsible_container \" aria-live=\"polite\" data-customize-animation=\"false\"><h3 class=\"bu_collapsible\" aria-expanded=\"false\"tabindex=\"0\" role=\"button\">General Electives<\/h3><div class=\"bu_collapsible_section\" style=\"display: none;\"><\/p>\n\n\n\n<p>(Four courses\/16 units)<\/p>\n\n\n\n<p>Students not choosing a concentration must complete four general electives. Students pursuing a concentration should review the requirements for&nbsp;<a href=\"https:\/\/www.bu.edu\/met\/degrees-certificates\/ms-applied-data-analytics-ai-machine-learning\/\" target=\"_blank\" rel=\"noreferrer noopener\">AI &amp; Machine Learning<\/a>&nbsp;or&nbsp;<a href=\"https:\/\/www.bu.edu\/met\/degrees-certificates\/ms-applied-data-analytics-data-engineering\/\" target=\"_blank\" rel=\"noreferrer noopener\">Data Engineering<\/a>.<\/p>\n\n\n\n<p>When choosing electives, students should make sure that they have all prerequisites required by the selected course. Note that some courses may not be available in an online format.<\/p>\n\n\n<p><div class=\"course-feed\"><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">664<\/span><\/span> Artificial Intelligence<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\"><\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 248 and MET CS 342. - Study of the ideas and techniques that enable computers to behave intelligently. Search, constraint propagations, and reasoning. Knowledge representation, natural language, learning, question answering, inference, visual perception, and\/or problem solving. Laboratory course.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Kalathur<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">M<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=MET\">MET 101<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O1, SPRG 2026 <span class=\"cf-section-dates\">Jan 13th to Mar 2nd<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Mansur<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">669<\/span><\/span> Database Design and Implementation for Business<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\"><\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Learn the latest relational and object-relational tools and techniques for persistent data and object modeling and management. You will gain extensive hands-on experience using Oracle or Microsoft SQL Server as you learn the Structured Query Language (SQL) and design and implement databases. You will design and implement a database system as a term project. Restrictions: This course may not be taken in conjunction with MET CS 469 (undergraduate) or MET CS 579. Only one of these courses can be counted towards degree requirements.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Diwania<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">R<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=CAS\">CAS B20<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O1, SPRG 2026 <span class=\"cf-section-dates\">Jan 13th to Mar 2nd<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Mansur<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O2, SPRG 2026 <span class=\"cf-section-dates\">Mar 10th to Apr 27th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Lee<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">688<\/span><\/span> Web Mining and Graph Analytics<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 544, or MET CS 555 or equivalent knowledge, or instructor's consent. - The Web Mining and Graph Analytics course covers the areas of web mining, machine learning fundamentals, text mining, clustering, and graph analytics. This includes learning fundamentals of machine learning algorithms, how to evaluate algorithm performance, feature engineering, content extraction, sentiment analysis, distance metrics, fundamentals of clustering algorithms, how to evaluate clustering performance, and fundamentals of graph analysis algorithms, link analysis and community detection based on graphs. Laboratory Course.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Hajiyani<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">M<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=FLR\">FLR 123<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O2, SPRG 2026 <span class=\"cf-section-dates\">Mar 10th to Apr 27th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Rawassizadeh<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">689<\/span><\/span> Designing and Implementing a Data Warehouse<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: CS 579 or CS 669 or consent of the instructor - This course surveys state-of-the art technologies in DW and Big Data. It describes logical, physical and semantic foundation of modern DW infrastructure. Students will create a cube using OLAP and implement decision support benchmarks on Hadoop\/Spark vs Vertica database. Upon successful completion, students will be familiar with tradeoffs in DW design and architecture.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O2, SPRG 2026 <span class=\"cf-section-dates\">Mar 10th to Apr 27th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Polnar<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">699<\/span><\/span> Data Mining<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 521, MET LB 103 and MET LB 104; and either MET CS 579 or MET CS 669;  or consent of instructor. - Study basic concepts and techniques of data mining. Topics include data preparation, classification, performance evaluation, association rule mining, regression and clustering. You will learn underlying theories of data mining algorithms in the class and practice those algorithms through assignments and a semester-long class project using R. After finishing this course, you will be able to independently perform data mining tasks to solve real-world problems.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A2, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Lee<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">W<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=MCS\">MCS B33<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O1, SPRG 2026 <span class=\"cf-section-dates\">Jan 13th to Mar 2nd<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Lee<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">766<\/span><\/span> Deep Reinforcement Learning<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 577 or consent of instructor. - This course focuses on reinforcement learning, covering fundamental concepts and advanced techniques. It begins with an introduction to reinforcement learning and key concepts, such as exploitation versus exploration and Markov Decision Processes. As the course progresses, it delves into state transition diagrams, the Bellman equation, and solutions to the Multi-Armed Bandits problem. Students will explore challenges and methods related to control and prediction. Then, they learn tabular methods, including Monte Carlo, Dynamic Programming, Temporal Difference Learning, SARSA, and Q-Learning. Afterwards, the course also extends into reviewing neural network concepts, covering convolutional and recurrent neural networks, and moves on to approximation methods for both discrete and continuous spaces, including DQN and its variants. Policy gradient methods, actor-critic methods. Finally, ethical considerations in AI and safety issues are also discussed.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Mohan<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">W<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=PHO\">PHO 201<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">767<\/span><\/span> Advanced Machine Learning and Neural Networks<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 521 and at least one of MET CS 577, MET CS 622, MET CS 673 or MET CS 682; or consent of instructor. Theories and methods for learning from data. The course covers a variety of approaches, including Supervised and Unsupervised Learning, Regression, k-means, KNN's, Neural Nets and Deep Learning, Transformers, Recurrent Neural Nets, Adversarial Learning, Bayesian Learning, and Genetic Algorithms. The underpinnings are covered: perceptron's, backpropagation, attention, and transformers. Each student creates a term project.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Mohan<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">R<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=MET\">MET 101<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O2, SPRG 2026 <span class=\"cf-section-dates\">Mar 10th to Apr 27th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Alizadeh-Shabdiz<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">777<\/span><\/span> Big Data Analytics<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisite: (MET CS 521 & MET CS 544 & MET CS 555) or MET CS 577 or consent of instructor. An introduction to large-scale data analytics, focusing on both the foundational concepts and practical tools used in the field. Big Data analytics involves extracting meaningful, non-trivial insights from vast and complex datasets. You will explore key software tools and programming techniques commonly used by data scientists working with distributed systems. You will also learn core technologies for storing and processing large volumes of data, with a particular emphasis on cluster computing frameworks that follow the MapReduce paradigm, including Hadoop MapReduce and Apache Spark. Through hands-on assignments and projects, you will gain practical experience by implementing data processing algorithms and running them on real-world cloud platforms such as Amazon Web Services (AWS) and Google Cloud, utilizing educational credits and accounts provided for the course.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Alizadeh-Shabdiz<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">M<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=MCS\">MCS B31<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">779<\/span><\/span> Advanced Database Management<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\"> Graduate Prerequisites: (METCS579 OR METCS669) or consent of the instructor - This course covers advanced aspects of database management including normalization and denormalization, query optimization, distributed databases, data warehousing, and big data. There is extensive coverage and hands on work with SQL, and database instance tuning. Course covers various modern database architectures including relational, key value, object relational and document store models as well as various approaches to scale out, integrate and implement database systems through replication and cloud based instances. Students learn about unstructured \"big data\" architectures and databases, and gain hands-on experience with Spark and MongoDB. Students complete a term project exploring an advanced database technology of their choice. Prereq: MET CS 579 or MET CS 669; or instructor's consent.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Polnar<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">R<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=CAS\">CAS 222<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section O1, SPRG 2026 <span class=\"cf-section-dates\">Jan 13th to Mar 2nd<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Polnar<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">787<\/span><\/span> AI and Cybersecurity<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\"><\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 577 or consent of instructor. This course provides an in-depth exploration of the critical intersection between Artificial Intelligence (AI) and cybersecurity, focusing on two interconnected themes: protecting AI systems from vulnerabilities and harnessing the power of AI to tackle cybersecurity challenges. As AI becomes a cornerstone of modern technology, ensuring the security of AI-powered systems against adversarial attacks, backdoor attacks, and model theft is essential. Simultaneously, AI offers transformative capabilities for malware detection, intrusion prevention, and malware analysis. Through a combination of theoretical foundations, hands-on exercises, and real-world case studies, students will delve into topics such as adversarial machine learning, backdoor injection and defense, IP protection, and privacy-preserving AI. They will also learn how to design and implement AI-driven tools for identifying and mitigating cyber threats in dynamic environments. The course emphasizes practical applications, encouraging students to build resilient AI systems and utilize advanced AI techniques to enhance system security and detect emerging threats. Hands-on labs based on existing tools are provided and required.<\/p>\n\t<\/div>\n\n\t\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">788<\/span><\/span> Generative AI<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 577, Python programming, mathematics required for machine learning, and familiarity with neural networks. Or consent of instructor. - The first part of the course covers statistical concepts required for generative artificial intelligence. We review regressions and optimization methods as well as traditional neural network architectures, including perceptron and multilayer perceptron. Next, we move to Convolutional Neural Networks and Recurrent Neural Networks and close this part with Attention and Transformers. The second part of the course focuses on generative neural networks. We start with traditional self-supervised learning algorithms (Self Organized Map and Restricted Boltzmann Machine), then explore Auto Encoder architectures and Generative Adversarial Networks and move toward architectures that construct generative models, including recent advances in NLP, including LLMs, and Retrieval Augmented Methods. Finally, we describe the Neural Radiance Field, 3D Gaussian Splatting, and text-2-image models.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Rawassizadeh<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">R<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=CAS\">CAS B06A<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">790<\/span><\/span> Computer Vision in AI<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">Prerequisites: MET CS 566 or instructor's consent. - Students enrolled in this course will gain comprehensive insights into fundamental and advanced concepts within the dynamic realm of computer vision. The curriculum will focus on cutting-edge applications of deep neural networks in computer vision. Through hands-on experiences and practical exercises, students will learn to leverage computer vision and machine learning techniques to solve real-world challenges. This course not only equips students with theoretical knowledge but empowers them to apply these concepts effectively, fostering a deep understanding of how computer vision can be harnessed to address complex problems in diverse industries.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\">Zhang<\/td>\n\t<td class=\"cf-section-type\">Independent<\/td>\n\t<td class=\"cf-section-day\">T<\/td>\n\t<td class=\"cf-section-start\">06:00:00 PM&ndash;08:45:00 PM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=CGS\">CGS 113<\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><\/div><\/p>\n\n\n<p><\/div>\n<\/div>\n\n\n\n<div class=\"bu_collapsible_container \" aria-live=\"polite\" data-customize-animation=\"false\"><h3 class=\"bu_collapsible\" aria-expanded=\"false\"tabindex=\"0\" role=\"button\">Master\u2019s Thesis Option<\/h3><div class=\"bu_collapsible_section\" style=\"display: none;\"><\/p>\n\n\n\n<p>(Two courses\/8 units)<\/p>\n\n\n\n<p>Students have the option to complete a master\u2019s thesis by taking two Master Thesis courses (8 units) in addition to the program\u2019s ten course (40 units) requirement. The thesis must be completed within 12 months and is available to MS in Applied Data Analytics candidates who have completed at least four courses toward their degree (not including foundation courses) and have a grade point average (GPA) of 3.7 or higher. Students are responsible for finding a thesis advisor and principal readers within the department. The advisor must be a full-time faculty member; the principal readers may be part-time faculty. Department approval is required.<\/p>\n\n\n<p><div class=\"course-feed\"><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">810<\/span><\/span> MS Thesis 1<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">This is the first course of the two-part thesis option available to Master\u2019s degree program candidates in the Department of Computer Science. You must have completed at least four courses toward your degree and have a grade point average (GPA) of 3.7 or higher. You are responsible for finding a thesis advisor and a principal reader within the department. Please refer to the Department for further details on the application process. Both MET CS 810 Master\u2019s Thesis 1 and MET CS 811 Master\u2019s Thesis 2 must be completed within 12 months.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\"><\/td>\n\t<td class=\"cf-section-type\">Directed Study<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A2, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\"><\/td>\n\t<td class=\"cf-section-type\">Directed Study<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A3, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\"><\/td>\n\t<td class=\"cf-section-type\">Directed Study<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><aside class=\"cf-course\">\n\t<div class=\"cf-course-card\">\n\t\t<h3 class=\"cf-course-title\"><span class=\"cf-course-id\"><span class=\"cf-course-college\">MET<\/span> <span class=\"cf-course-dept\">CS<\/span> <span class=\"cf-course-number\">811<\/span><\/span> Master's Thesis 2<\/h3>\n\t\t<p class=\"meta cf-course-info\"><span class=\"cf-course-credits\">4 credits.<\/span> <span class=\"cf-course-offered\">Fall and Spring<\/span> <span class=\"cf-course-prereqs\"><\/span><\/p>\n        \n\t\t<p class=\"cf-course-description\">This is the second course of the two-part thesis option available to Master\u2019s degree program candidates in the Department of Computer Science. You must have completed at least four courses toward your degree and have a grade point average (GPA) of 3.7 or higher. You are responsible for finding a thesis advisor and a principal reader within the department. Please refer to the Department for further details on the application process. Both METCS 810 Master\u2019s Thesis 1 and METCS 811 Master\u2019s Thesis 2 must be completed within 12 months.<\/p>\n\t<\/div>\n\n\t<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\"><\/td>\n\t<td class=\"cf-section-type\">Directed Study<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A2, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\"><\/td>\n\t<td class=\"cf-section-type\">Directed Study<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div><div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A3, SPRG 2026 <span class=\"cf-section-dates\">Jan 20th to Apr 30th<\/span><\/caption>\n\t<thead class=\"cf-section-header\">\n\t\t<tr>\n\t\t\t<th class=\"cf-section-instructortitle\">Instructor<\/th>\n\t\t\t<th class=\"cf-section-typetitle\">Type<\/th>\n\t\t\t<th class=\"cf-section-daytitle\">Days<\/th>\n\t\t\t<th class=\"cf-section-timestitle\">Times<\/th>\n\t\t\t<th class=\"cf-section-locationtitle\">Location<\/th>\n\t\t<\/tr>\n\t<\/thead>\n\t<tbody>\n\t\t<tr class=\"cf-section-item\">\n\t<td class=\"cf-section-instructor\"><\/td>\n\t<td class=\"cf-section-type\">Directed Study<\/td>\n\t<td class=\"cf-section-day\">ARR<\/td>\n\t<td class=\"cf-section-start\">12:00:00 AM&ndash;12:00:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=\"> <\/a><\/td>\n<\/tr>\n\t<\/tbody>\n<\/table>\n<\/div>\n<\/aside><\/div><\/p>\n\n\n<p><\/div>\n<\/div>\n\n\n\n\n<div class=\"wp-block-group alignwide program-block program-block--requirements program-block--type-degrees\"><div class=\"wp-block-group__inner-container\">\n<div class=\"wp-block-columns program-block--requirements__inner\">\n<div class=\"wp-block-column program-block--requirements__content\">\n<div class=\"wp-block-group program-block--requirements__group\"><div class=\"wp-block-group__inner-container\">\n<h3 class=\"program-block--requirements__group-title\"><a href=\"https:\/\/www.bu.edu\/met\/admissions\/academic-calendars\/online-calendar\/\" target=\"_blank\" rel=\"noreferrer noopener\">Dates &amp; Deadlines<\/a><\/h3>\n\n\n\n<p class=\"program-block--requirements__group-text\">View BU MET\u2019s academic calendar for online programs, including important dates and deadlines.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group program-block--requirements__group\"><div class=\"wp-block-group__inner-container\">\n<h3 class=\"program-block--requirements__group-title\"><a href=\"https:\/\/www.bu.edu\/met\/admissions\/apply-now-graduate\/\" target=\"_blank\" rel=\"noreferrer noopener\">Application Requirements<\/a><\/h3>\n\n\n\n<p class=\"program-block--requirements__group-text\">Learn about application requirements for BU MET graduate degree and certificate programs.<\/p>\n<\/div><\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column program-block--requirements__media\">\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"1024\" height=\"576\" src=\"\/online\/files\/2025\/10\/shutterstock_2494681135.jpg\" alt=\"A woman reviews several data charts across three computer monitors in a large office\" class=\"wp-image-6449\" srcset=\"https:\/\/www.bu.edu\/online\/files\/2025\/10\/shutterstock_2494681135.jpg 1024w, https:\/\/www.bu.edu\/online\/files\/2025\/10\/shutterstock_2494681135-636x358.jpg 636w, https:\/\/www.bu.edu\/online\/files\/2025\/10\/shutterstock_2494681135-768x432.jpg 768w, https:\/\/www.bu.edu\/online\/files\/2025\/10\/shutterstock_2494681135-992x558.jpg 992w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n<h2>How You Benefit from a <br>Boston University Education<\/h2>\n\n\n\n<p>A BU credential can help lay the foundation for career advancement and personal success.<\/p>\n\n\n\n<ul><li>Benefit from an average 24:1 student-to-instructor ratio.<\/li><li>Work closely with highly qualified faculty and industry leaders who have substantial backgrounds and achievements in data analytics, data science, data storage technologies, cybersecurity, artificial intelligence (AI), machine learning, software development, and many other areas.<\/li><li>Gain in-depth, practical experience with the latest technologies through case studies and real-world projects.<\/li><li>Experience a supportive online network, with courses developed and taught by PhD-level full-time faculty and professionals with hands-on expertise in the industry.<\/li><li>Learn from the best\u2014BU MET\u2019s Department of Computer Science was established in 1979 and is the longest-running computer science department at BU. Over the course of its existence, the department has played an important role in the emergence of IT at the University and throughout the region.<\/li><\/ul>\n\n\n\n<p>All graduate students are automatically considered for merit scholarships during the application process and nominated based on eligibility. <a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/admissions\/financial-aid\/scholarships\/merit-scholarships\/\" target=\"_blank\">Learn more.<\/a><\/p>\n\n\n\n<h2>Rankings &amp; Accreditations<\/h2>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column is-vertically-aligned-center\" style=\"flex-basis:20%\">\n<div class=\"wp-block-image program-block--accolades-with-text__card-media\"><figure class=\"aligncenter size-large\"><a href=\"https:\/\/www.usnews.com\/education\/online-education\/boston-university-OCIT0007\/computer-information-technology\" target=\"_blank\" rel=\"noopener noreferrer\"><img loading=\"lazy\" width=\"300\" height=\"312\" src=\"\/online\/files\/2025\/10\/us-news-grad-infotech-2026.png\" alt=\"U.S. News &amp; World Report - Best Online Programs - Grad Information Technology - 2026\" class=\"wp-image-7921\"\/><\/a><\/figure><\/div>\n\n\n\n<p><\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-vertically-aligned-center\" style=\"flex-basis:80%\">\n<p class=\"has-normal-font-size\"><strong><strong>#12, Best Online Master&#8217;s in Computer Information Technology Programs<\/strong><\/strong><\/p>\n\n\n\n<p class=\"has-small-font-size\">MET\u2019s online master\u2019s degrees in computer information technology are ranked #12 in the nation by <em>U.S. News &amp; World Report<\/em>.<\/p>\n<\/div>\n<\/div>\n\n\n\n<p><\/p>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column is-vertically-aligned-center\" style=\"flex-basis:20%\">\n<div class=\"wp-block-image program-block--accolades-with-text__card-media\"><figure class=\"aligncenter size-large\"><img src=\"\/online\/files\/2026\/02\/BU-Online-MS-DA-by-TechGuide_cropped.jpg\" alt=\"#2 Best Online Master\u2019s in Data Analytics of 2026\" class=\"wp-image-7207\"\/><\/figure><\/div>\n\n\n\n<p><\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-vertically-aligned-center\" style=\"flex-basis:80%\">\n<p><strong>#2 Best Online Master\u2019s in Data Analytics of 2026<\/strong><\/p>\n\n\n\n<p class=\"has-small-font-size\">BU MET\u2019s MS in Applied Data Analytics is ranked #2 Best Online Master\u2019s in Data Analytics Degree Programs for 2026 by&nbsp;<a href=\"https:\/\/techguide.org\/analytics\/online-masters-in-data-analytics\/\" target=\"_blank\" rel=\"noopener\">TechGuide<\/a>.<\/p>\n<\/div>\n<\/div>\n\n\n\n<h3>Graduate with Analytics Expertise<\/h3>\n\n\n\n<p>Graduates of Metropolitan College\u2019s Applied Data Analytics master\u2019s degree will be able to demonstrate:<\/p>\n\n\n\n<ul><li>Knowledge of the foundations of applied probability and statistics and their relevance in day-to-day data analysis.<\/li><li>The ability to apply various data visualization techniques using real-world data sets and analyze the graphs and charts.<\/li><li>Knowledge of web analytics and metrics, procuring and processing unstructured text\/data, and the ability to investigate hidden patterns.<\/li><li>Knowledge-discovery skills using data mining techniques and tools over large amounts of data.<\/li><li>The ability to implement machine learning algorithms and recognize their pertinence in real-world applications.<\/li><li>Comprehensive knowledge of data analytics techniques, skills, and critical thinking, and an understanding of the possibilities and limitations of their applications.<\/li><\/ul>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-group alignwide program-block program-block--career-paths program-block--type-degrees\"><div class=\"wp-block-group__inner-container\">\n<div class=\"wp-block-group program-block--career-paths__footer\"><div class=\"wp-block-group__inner-container\">\n<div class=\"wp-block-columns program-block--career-paths__footer-inner\">\n<div class=\"wp-block-column program-block--career-paths__footer-header\">\n<h3 class=\"program-block--career-paths__footer-title\">Career Outcomes<\/h3>\n<\/div>\n\n\n\n<div class=\"wp-block-column program-block--career-paths__footer-card\">\n<h4 class=\"program-block--career-paths__footer-card-title\"><\/h4>\n\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container\">\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container\">\n<p><strong><strong>Employment of data scientists is projected to grow 36% from 2021 to 2031, with demand expected to grow much faster than average<\/strong><\/strong>.<\/p>\n\n\n\n<p class=\"program-block--career-paths__footer-card-text\">Source: Bureau of Labor Statistics<\/p>\n<\/div><\/div>\n<\/div><\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column program-block--career-paths__footer-card\">\n<h4 class=\"program-block--career-paths__footer-card-title\"><\/h4>\n\n\n\n<p class=\"program-block--career-paths__footer-card-text\"><strong><strong>Increased demand for data scientists will stem from increased demand for data-driven decisions. Organizations will need more data scientists to mine and analyze the large amounts of information and data collected<\/strong><\/strong>.<\/p>\n\n\n\n<p>Source: Bureau of Labor Statistics<\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column\">\n<h4><\/h4>\n\n\n\n<p><strong><strong>$103,500<\/strong><\/strong><\/p>\n\n\n\n<p>Median annual wage for Data Scientists, May 2023<br><br>Source: Bureau of Labor Statistics<\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column is-vertically-aligned-center\" style=\"flex-basis:20%\">\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-medium\"><img src=\"\/online\/files\/2025\/05\/MelissaViator-Headshot.jpg\" style=\"width: 150px; height: auto; border: 2px solid #04c5e7;\" alt=\"Melissa Viator headshot\" class=\"wp-image-3676\"><\/figure><\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-vertically-aligned-center\" style=\"flex-basis:80%\">\n<p>\u201cThis program led me to my current position as a data scientist at Boston\u2019s Massachusetts General Hospital, where I implement machine learning models to improve the hospital\u2019s operational efficiency and support physicians with clinical research. I am immensely happy with my investment in graduate school, as it led me to many amazing opportunities!\u201d&nbsp;<a href=\"https:\/\/www.bu.edu\/met\/programs\/computer-science-it\/stories\/melissa-viator\/\" target=\"_blank\" rel=\"noreferrer noopener\">Read&nbsp;more.<\/a><\/p>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column is-vertically-aligned-center\" style=\"flex-basis:20%\"><\/div>\n\n\n\n<div class=\"wp-block-column is-vertically-aligned-center\" style=\"flex-basis:80%\">\n<p class=\"has-small-font-size\"><strong>Melissa Viator (MET\u201923)<\/strong><br><strong><strong>Data Scientist, Massachusetts General Hospital<\/strong><\/strong><br><em>MS, Applied Data Analytics<\/em><\/p>\n<\/div>\n<\/div>\n\n\n\n<h3>Advance Your Career<\/h3>\n\n\n\n<p>BU MET\u2019s Applied Data Analytics master\u2019s prepares you for a wealth of different roles, such as Data Science Analyst, Senior Emerging Tech Engineer, Solution Specialist, Senior Data Architect, Senior Strategy Product Manager, Senior Audit Analyst, Data Scientist, Economist, Business Intelligence Analyst, Chief Analytics Officer, and Analytics Manager.<\/p>\n\n\n\n<p><strong>Recent graduates have found job opportunities and career paths at companies such as:<\/strong><\/p>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column\">\n<ul><li>Fidelity Investments<\/li><li>Akamai Technologies<\/li><li>Amazon Web Services (AWS)<\/li><li>Chi Alpha Campus Ministries<\/li><li>Deloitte Consulting<\/li><\/ul>\n<\/div>\n\n\n\n<div class=\"wp-block-column\">\n<ul><li>Drew University<\/li><li>McKesson<\/li><li>Olympus Americas<\/li><li>Travelers<\/li><li>Turiyatree Technologies<\/li><\/ul>\n<\/div>\n<\/div>\n\n\n\n<h4>Take Advantage of Career Resources at BU MET<\/h4>\n\n\n\n<p>You will find the support you need in reaching your career goals through <a href=\"https:\/\/www.bu.edu\/met\/careers\/\" target=\"_blank\" rel=\"noreferrer noopener\">MET\u2019s Career Development office<\/a>, which&nbsp;offers a variety of job-hunting resources, including one-on-one career counseling by appointment for online students. You can also take advantage of tools and resources available online through&nbsp;<a href=\"https:\/\/www.bu.edu\/careers\/\" target=\"_blank\" rel=\"noreferrer noopener\">BU\u2019s Center for Career Development<\/a>.<\/p>\n\n\n\n<div class=\"wp-block-group alignwide program-block program-block--featured-faculty program-block--type-programs\"><div class=\"wp-block-group__inner-container\">\n<div class=\"wp-block-group program-block--featured-faculty__inner\"><div class=\"wp-block-group__inner-container\">\n<h2 style=\"padding-top: 1.5em; margin-bottom: 0; text-align: center; color: #fff;\">Computer Science Faculty<\/h2>\n\n\n\n<div class=\"wp-block-columns program-block--featured-faculty__list\">\n<div class=\"wp-block-column program-block--featured-faculty__faculty\">\n<h3 class=\"has-text-align-left program-block--featured-faculty__faculty-name\"><a href=\"https:\/\/www.bu.edu\/met\/profile\/guanglan-zhang\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Guanglan Zhang<\/strong><\/a><\/h3>\n\n\n\n<p>Associate Professor, Computer Science<\/p>\n\n\n\n<p>Coordinator, Health Informatics Programs<\/p>\n\n\n\n<p>Chair, Computer Science<\/p>\n\n\n\n<figure class=\"wp-block-image size-large program-block--featured-faculty__faculty-image\"><img loading=\"lazy\" width=\"1024\" height=\"900\" src=\"\/online\/files\/2025\/05\/Guanglan_Zhang_Headshot_Canto-1-1024x900.jpg\" alt=\"Headshot of Guanglan Zhang\" class=\"wp-image-2774\" srcset=\"https:\/\/www.bu.edu\/online\/files\/2025\/05\/Guanglan_Zhang_Headshot_Canto-1-1024x900.jpg 1024w, https:\/\/www.bu.edu\/online\/files\/2025\/05\/Guanglan_Zhang_Headshot_Canto-1-636x559.jpg 636w, https:\/\/www.bu.edu\/online\/files\/2025\/05\/Guanglan_Zhang_Headshot_Canto-1-768x675.jpg 768w, https:\/\/www.bu.edu\/online\/files\/2025\/05\/Guanglan_Zhang_Headshot_Canto-1-1536x1350.jpg 1536w, https:\/\/www.bu.edu\/online\/files\/2025\/05\/Guanglan_Zhang_Headshot_Canto-1-2048x1800.jpg 2048w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column program-block--featured-faculty__faculty\">\n<h3 class=\"has-text-align-left program-block--featured-faculty__faculty-name\"><a href=\"https:\/\/www.bu.edu\/met\/profile\/shengzhi-zhang\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Shengzhi Zhang<\/strong><\/a><\/h3>\n\n\n\n<p>Associate Professor<\/p>\n\n\n\n<p>Associate Chair, Computer Science<\/p>\n\n\n\n<p>Coordinator, Web Application Development<\/p>\n\n\n\n<figure class=\"wp-block-image size-large program-block--featured-faculty__faculty-image\"><img loading=\"lazy\" width=\"683\" height=\"1024\" src=\"\/online\/files\/2025\/05\/Shengzhi_Zhang_0023-1-683x1024.jpg\" alt=\"Headshot of Shengzhi Zhang\" class=\"wp-image-2776\" srcset=\"https:\/\/www.bu.edu\/online\/files\/2025\/05\/Shengzhi_Zhang_0023-1-683x1024.jpg 683w, https:\/\/www.bu.edu\/online\/files\/2025\/05\/Shengzhi_Zhang_0023-1-424x636.jpg 424w, https:\/\/www.bu.edu\/online\/files\/2025\/05\/Shengzhi_Zhang_0023-1-768x1152.jpg 768w, https:\/\/www.bu.edu\/online\/files\/2025\/05\/Shengzhi_Zhang_0023-1-1024x1536.jpg 1024w, https:\/\/www.bu.edu\/online\/files\/2025\/05\/Shengzhi_Zhang_0023-1-1365x2048.jpg 1365w\" sizes=\"(max-width: 683px) 100vw, 683px\" \/><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column program-block--featured-faculty__faculty\">\n<h3><a href=\"https:\/\/www.bu.edu\/met\/profile\/suresh-kalathur\/\" target=\"_blank\" rel=\"noreferrer noopener\">Suresh Kalathur<\/a><\/h3>\n\n\n\n<p>Assistant Professor, Computer Science<\/p>\n\n\n\n<p>Director, Analytics<\/p>\n\n\n\n<figure class=\"wp-block-image size-large program-block--featured-faculty__faculty-image\"><img src=\"https:\/\/www.bu.edu\/met\/files\/2020\/09\/Suresh-Kalathur-nw.jpg\" alt=\"Suresh Kalathur headshot\" class=\"wp-image-5959\"\/><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column\">\n<h3><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/farshid-alizadeh-shabdiz\/\" target=\"_blank\">Farshid Alizadeh Shabdiz<\/a><\/h3>\n\n\n\n<p>Professor of the Practice, Computer Science<\/p>\n\n\n\n<figure class=\"wp-block-image size-large program-block--featured-faculty__faculty-image\"><img src=\"\/online\/files\/2025\/12\/Farshid_headshot_300x300.jpg\" alt=\"Farshid Alizadeh Shabdiz\" class=\"wp-image-5248\"\/><\/figure>\n<\/div>\n<\/div>\n<\/div><\/div>\n<\/div><\/div>\n\n\n<div class=\"bu_collapsible_container \" aria-live=\"polite\" data-customize-animation=\"false\"><h3 class=\"bu_collapsible\" aria-expanded=\"false\"tabindex=\"0\" role=\"button\">View All Faculty<\/h3><div class=\"bu_collapsible_section\" style=\"display: none;\"><\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/scott-arena\/\" target=\"_blank\">Scott Arena<\/a><\/strong><\/strong><br>Master Lecturer, Computer Science <br>Coordinator, Computer Networks<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/eric-j-braude\/\" target=\"_blank\">Eric Braude<\/a><\/strong><\/strong><br>Associate Professor<br>Director of Digital Learning, Computer Science<br>Coordinator, Computer Information Systems<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/lou-chitkushev\/\" target=\"_blank\">Lou Chitkushev<\/a><\/strong><\/strong><br>Senior Associate Dean for Academic Affairs<br>Associate Professor, Computer Science<br>Director, Health Informatics &amp; Health Sciences<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/john-day\/\" target=\"_blank\">John Day<\/a><\/strong><\/strong><br>Master Lecturer, Computer Science<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/andrew-gorlin\/\" target=\"_blank\">Andrew Gorlin<\/a><\/strong><\/strong><br>Lecturer, Computer Science<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/vijay-kanabar\/\" target=\"_blank\">Vijay Kanabar<\/a><\/strong><\/strong><br>Associate Professor, Computer Science and Administrative Sciences<br>Director, Project Management Programs<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/jae-young-lee\/\" target=\"_blank\">Jae Young Lee<\/a><\/strong><\/strong><br>Assistant Professor, Computer Science<br>Coordinator, Databases<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/avinash-mohan\/\" target=\"_blank\">Avinash Mohan<\/a><\/strong><\/strong><br>Assistant Professor, Computer Science<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/eugene-pinsky\/\" target=\"_blank\">Eugene Pinsky<\/a><\/strong><\/strong><br>Associate Professor of the Practice, Computer Science<br>Coordinator, Software Development<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/reza-rawassizadeh\/\" target=\"_blank\">Reza Rawassizadeh<\/a><\/strong><\/strong><br>Associate Professor, Computer Science<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/maryan-rizinski\/\" target=\"_blank\">Maryan Rizinski<\/a><\/strong><\/strong><br>Associate Professor of the Practice, Computer Science<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/anatoly-temkin\/\" target=\"_blank\">Anatoly Temkin<\/a><\/strong><\/strong><br>Assistant Professor Emeritus, Computer Science<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/ming-zhang\/\" target=\"_blank\">Ming Zhang<\/a><\/strong><\/strong><br>Assistant Professor, Computer Science<br>Coordinator, BSCS Programs<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/yuting-zhang\/\" target=\"_blank\" data-type=\"URL\" data-id=\"https:\/\/www.bu.edu\/met\/profile\/yuting-zhang\/\">Yuting Zhang<\/a><\/strong><\/strong><br>Assistant Professor, Computer Science<br>Director, Cybersecurity<br>Coordinator, Computer Systems &amp; Digital Forensics<\/p>\n\n\n\n<p><strong><strong><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bu.edu\/met\/profile\/tanya-zlateva\/\" target=\"_blank\">Tanya Zlateva<\/a><\/strong><\/strong><br>Dean, Metropolitan College &amp; Extended Education<br>Professor of the Practice, Computer Science and Education<br>Education Director, Information Security, Center for Reliable Information Systems &amp; Cyber Security<\/p>\n\n\n<p><\/div>\n<\/div>\n\n\n\n\n<hr class=\"wp-block-separator is-style-default\"\/>\n\n\n\n<h2 class=\"has-text-align-center\">Interested in Learning More?<\/h2>\n\n\n\n<p><\/p>\n\n\n\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column\">\n<div class=\"wp-block-buttons is-content-justification-center\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link\" href=\"https:\/\/www.bu.edu\/met\/events\/\" target=\"_blank\" rel=\"noreferrer noopener\">MET Events<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column\">\n<div class=\"wp-block-buttons is-content-justification-center\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link\" href=\"https:\/\/www.bu.edu\/met\/admissions\/tuition-and-fees\/\" target=\"_blank\" rel=\"noreferrer noopener\">Tuition &amp; Fees<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column\">\n<div class=\"wp-block-buttons is-content-justification-center\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link\" href=\"https:\/\/www.bu.edu\/met\/admissions\/financial-aid\/\" target=\"_blank\" rel=\"noreferrer noopener\">Financial Aid<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Develop In-Demand Data Analytics Skills With data analytics needs influencing every major industry\u2014including health care, tech, finance, communication, entertainment, energy, transportation, government, and manufacturing, to name some\u2014there is significant growth in specialized data science and machine learning areas. The demand for skilled talent continues to outpace supply, with McKinsey Global Institute anticipating a shortfall of [&hellip;]<\/p>\n","protected":false},"author":23559,"featured_media":2421,"parent":4319,"menu_order":2,"template":"","meta":{"_editor_template":"featured-faculty-template"},"bu_progs_page-type":[6],"bu_progs_degree-option":[76],"bu_progs_schools-colleges":[121],"bu_progs_education-level":[108],"bu_progs_area-of-study":[128,118],"bu_progs_area-of-interest":[],"bu_progs_department-affiliation":[],"bu_progs_format":[112,111],"bu_progs_availability":[114,115],"bu_progs_location":[117,116],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu-program-page\/2405"}],"collection":[{"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu-program-page"}],"about":[{"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/types\/bu-program-page"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/users\/23559"}],"version-history":[{"count":45,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu-program-page\/2405\/revisions"}],"predecessor-version":[{"id":8016,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu-program-page\/2405\/revisions\/8016"}],"up":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu-program-page\/4319"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/media\/2421"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/media?parent=2405"}],"wp:term":[{"taxonomy":"bu_progs_page-type","embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu_progs_page-type?post=2405"},{"taxonomy":"bu_progs_degree-option","embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu_progs_degree-option?post=2405"},{"taxonomy":"bu_progs_schools-colleges","embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu_progs_schools-colleges?post=2405"},{"taxonomy":"bu_progs_education-level","embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu_progs_education-level?post=2405"},{"taxonomy":"bu_progs_area-of-study","embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu_progs_area-of-study?post=2405"},{"taxonomy":"bu_progs_area-of-interest","embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu_progs_area-of-interest?post=2405"},{"taxonomy":"bu_progs_department-affiliation","embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu_progs_department-affiliation?post=2405"},{"taxonomy":"bu_progs_format","embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu_progs_format?post=2405"},{"taxonomy":"bu_progs_availability","embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu_progs_availability?post=2405"},{"taxonomy":"bu_progs_location","embeddable":true,"href":"https:\/\/www.bu.edu\/online\/wp-json\/wp\/v2\/bu_progs_location?post=2405"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}