{"id":7536,"date":"2026-02-02T12:29:41","date_gmt":"2026-02-02T17:29:41","guid":{"rendered":"https:\/\/www.bu.edu\/online\/?post_type=bu-program-page&#038;p=7536"},"modified":"2026-07-10T09:48:43","modified_gmt":"2026-07-10T13:48:43","slug":"applied-ai-machine-learning-graduate-certificate","status":"publish","type":"bu-program-page","link":"https:\/\/www.bu.edu\/online\/degrees-certificates\/computer-science-it\/applied-ai-machine-learning-graduate-certificate\/","title":{"rendered":"Online Applied AI &#038; Machine Learning Graduate Certificate"},"content":{"rendered":"\n<h2>Build Practical, Dynamic Artificial Intelligence Skills to Advance Your Career Across Industries<\/h2>\n\n\n\n<p>The Graduate Certificate in Applied AI &amp; Machine Learning at Boston University\u2019s Metropolitan College (BU MET) introduces online learners seeking industry-relevant AI skills to key topics in the field, including neural networks, generative AI, AI security, intelligent image processing, reinforcement learning, automated reasoning, and ethical considerations in AI. <\/p>\n\n\n\n<p>Designed to prepare you for roles like machine learning engineer, AI developer, data scientist, computer vision expert, ethical AI analyst, natural language processing (NLP) specialist, and AI product manager, the curriculum emphasizes hands-on experience with real-world AI applications. Through practical projects, you\u2019ll learn how to design, develop, and deploy intelligent systems across multiple industries, leaving you prepared to meet the growing workforce demand for AI professionals in today\u2019s technology-driven world. <\/p>\n\n\n\n<p>The Graduate Certificate in Applied AI &amp; Machine Learning is also available on campus in Boston.&nbsp;<a href=\"https:\/\/www.bu.edu\/met\/degrees-certificates\/applied-ai-machine-learning-graduate-certificate\/\" target=\"_blank\" rel=\"noopener\">Learn more.<\/a><\/p>\n\n\n\n<h2>Curriculum<\/h2>\n\n\n\n<p>The online Graduate Certificate in Applied AI &amp; Machine Learning consists of four required courses (16 units).<\/p>\n\n\n\n<p>Academic units earned toward the online Graduate Certificate in Applied AI &amp; Machine Learning may be transferred to the Master of Science in Computer Science concentration in <a href=\"https:\/\/www.bu.edu\/met\/degrees-certificates\/ms-computer-science-ai-machine-learning\/\" target=\"_blank\" rel=\"noopener\">AI &amp; Machine Learning<\/a>. Please note that the MS in Computer Science is only offered on campus.<\/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\">Courses<\/h3><div class=\"bu_collapsible_section\" style=\"display: none;\"><\/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\">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 A2, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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=EPC\">EPC 206<\/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 A4, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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\">09:00:00 AM&ndash;11:45:00 AM<\/td>\n\t<td class=\"cf-section-location\"><a href=\"http:\/\/www.bu.edu\/maps\/?search=STH\">STH 113<\/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, FALL 2026 <span class=\"cf-section-dates\">Oct 27th to Dec 14th<\/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><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, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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\">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=SCI\">SCI 115<\/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, FALL 2026 <span class=\"cf-section-dates\">Sep 1st to Oct 19th<\/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\">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, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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\">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=CAS\">CAS 204A<\/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, FALL 2026 <span class=\"cf-section-dates\">Oct 27th to Dec 14th<\/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><\/div><\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><div style=\"border-top: 1px solid #ddd;\">\n<p style=\"font-weight: bold; font-style: italic; font-size: 105%; margin-top: 20px;\">And one course from the following:<\/p>\n\n<\/div><\/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\">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, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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\">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=CAS\">CAS 228<\/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, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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\">Vasilkoski<\/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=HAR\">HAR 220<\/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, FALL 2026 <span class=\"cf-section-dates\">Sep 1st to Oct 19th<\/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 A1, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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=SOC\">SOC B63<\/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, FALL 2026 <span class=\"cf-section-dates\">Oct 27th to Dec 14th<\/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 767 or consent of instructor. - Investigate reinforcement learning, focusing on fundamental concepts and advanced techniques. You will begin with an introduction to reinforcement learning and key concepts, such as exploitation versus exploration and Markov Decision Processes. Then, as the course progresses, you will delve into state transition diagrams, the Bellman equation, and solutions to the Multi-Armed Bandits problem. Challenges and methods for control and prediction will be explored, as well as tabular methods such as Monte Carlo, Dynamic Programming, Temporal Difference Learning, SARSA, and Q-Learning. The course culminates in a review of neural network concepts, covering convolutional and recurrent neural networks, and approximation methods for both discrete and continuous spaces, including DQN and its variants. Policy gradient methods, actor-critic methods, and 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, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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\">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=CAS\">CAS 426<\/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\">Prerequisites: (MET CS 521 & MET CS 544 & MET CS 555) or MET CS 577 or consent of instructor. An overview of the principles and practice of large-scale data analytics. You will examine methods for extracting meaningful insights from large, complex, and distributed datasets, learning about core technologies for storing and processing high-volume data. This course emphasizes distributed computing frameworks based on the MapReduce paradigm, including Hadoop MapReduce and Apache Spark, along with programming models, parallel data processing, and performance considerations in cluster-based environments. Through hands-on assignments and projects, you will implement data processing algorithms and deploy them on cloud platforms such as Amazon Web Services (AWS) and Google Cloud, developing the practical skills required for data engineering and large-scale analytics in real-world environments. Educational cloud accounts and credits are provided.<\/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, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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 218<\/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, FALL 2026 <span class=\"cf-section-dates\">Sep 1st to Oct 19th<\/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\">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<div class=\"responsive-table cf-section-wrapper\">\n<table class=\"cf-table\">\n\t<caption class=\"cf-section-title\">Section A1, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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\">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=BRB\">BRB 121<\/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\">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, FALL 2026 <span class=\"cf-section-dates\">Sep 2nd to Dec 10th<\/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\">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 233<\/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, FALL 2026 <span class=\"cf-section-dates\">Oct 27th to Dec 14th<\/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\">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 O2, FALL 2026 <span class=\"cf-section-dates\">Oct 27th to Dec 14th<\/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\n<div style=\"height:60px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\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=\"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=\"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 src=\"\/online\/files\/2026\/02\/middle-cs-ai-ml-shutterstock_2652529017.jpg\" alt=\"A digital image of data points rising up to resemble a digital brain\" class=\"wp-image-5813\"\/><\/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 hands-on involvement in data analytics, data science, data storage technologies, cybersecurity, artificial intelligence (AI), machine learning, software development, and many other areas.<\/li><li>BU MET\u2019s computer science courses ensure you get the attention you need, while introducing case studies and real-world projects that emphasize technical and theoretical knowledge\u2014combining in-depth, practical experience with the critical skills needed to remain on the forefront of the information technology field.<\/li><li>BU 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<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\"><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\" style=\"max-width: 150px\" \/><\/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&#8217;s computer science &amp; IT graduate certificates share curriculum with MET&#8217;s online master&#8217;s degrees in computer information technology, which 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<h3>Graduate with Applied AI &amp; Machine Learning Expertise<\/h3>\n\n\n\n<p>Students who complete the Graduate Certificate in Applied AI &amp; Machine Learning will be able to:<\/p>\n\n\n\n<ul><li>Solve complex problems such as computer vision, natural language processing, and speech recognition using machine learning algorithms, including supervised and unsupervised learning models, neural network architectures, and deep learning techniques.<\/li><li>Design and implement agents and algorithms for self-learning systems, leveraging AI models for data representation and prediction, implementing evolutionary and genetic algorithms for optimization, and developing software systems that incorporate AI models to enhance capabilities.<\/li><li>Evaluate the ethical implications of AI systems, ensuring model fairness, accountability, and transparency, and effectively communicating technical AI concepts to non-technical stakeholders.<\/li><\/ul>\n\n\n\n<h3>Advance Your Career<\/h3>\n\n\n\n<p>BU MET&#8217;s Graduate Certificate in Applied AI &amp; Machine Learning prepares you for a wealth of different roles, such as machine learning engineer, AI developer, data scientist, computer vision expert, ethical AI analyst, natural language processing (NLP) specialist, and AI product manager.<\/p>\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=\"noopener\">MET\u2019s Career Development office<\/a>, which 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=\"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\n\n\n<p><\/p>\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 class=\"has-text-align-left program-block--featured-faculty__faculty-name\"><a href=\"https:\/\/www.bu.edu\/met\/profile\/reza-rawassizadeh\/\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>Reza Rawassizadeh<\/strong><\/a><\/h3>\n\n\n\n<p>Associate Professor, Computer Science<\/p>\n\n\n\n<figure class=\"wp-block-image size-large program-block--featured-faculty__faculty-image\"><img src=\"https:\/\/www.bu.edu\/online\/files\/2026\/03\/headshot-Rawassizadeh-26.jpg\" alt=\"Headshot of Reza Rawassizadeh\" class=\"wp-image-2774\"\/><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column program-block--featured-faculty__faculty\">\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>Scot Arena<\/strong><br>Master Lecturer, Computer Science<br> Coordinator, Computer Networks<\/p>\n\n\n\n<p><strong>Lou Chitkushev<\/strong><br>Professor, Computer Science<br>\nSenior Associate Dean, Academic Affairs<br>\nDirector, Health Informatics &amp; Health Sciences<br>\nHead, Digital Forensics Research Laboratory<\/p>\n\n\n\n<p><strong>John Day<\/strong><br>Master Lecturer, Computer Science<\/p>\n\n\n\n<p><strong>Andrew Gorlin<\/strong><br>Lecturer, Computer Science<\/p>\n\n\n\n<p><strong>Suresh Kalathur<\/strong><br>Assistant Professor, Computer Science <br>Director, Analytics<\/p>\n\n\n\n<p><strong>Vijay Kanabar<\/strong><br>Associate Professor, Computer Science and Administrative Sciences<br>Director, Project Management Programs<\/p>\n\n\n\n<p><strong>Jae Young Lee<\/strong><br>Assistant Professor, Computer Science <br>Coordinator, Databases<\/p>\n\n\n\n<p><strong>Avinash Mohan<\/strong><br>Assistant Professor, Computer Science<\/p>\n\n\n\n<p><strong>Eugene Pinsky<\/strong><br>Associate Professor of the Practice, Computer Science<br>\nCoordinator, Software Development<\/p>\n\n\n\n<p><strong>Maryan Rizinski<\/strong><br>Associate Professor of the Practice, Computer Science<\/p>\n\n\n\n<p><strong>Anatoly Temkin<\/strong><br>Assistant Professor Emeritus, Computer Science<\/p>\n\n\n\n<p><strong>Ming Zhang<\/strong><br>Assistant Professor, Computer Science<br>Coordinator, BSCS Programs<\/p>\n\n\n\n<p><strong>Yuting Zhang<\/strong><br>Assistant Professor, Computer Science<br>Director, Cybersecurity<br>Coordinator, Computer Systems &amp; Digital Forensics<\/p>\n\n\n\n<p><strong>Tanya Zlateva<\/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>Build Practical, Dynamic Artificial Intelligence Skills to Advance Your Career Across Industries The Graduate Certificate in Applied AI &amp; Machine Learning at Boston University\u2019s Metropolitan College (BU MET) introduces online learners seeking industry-relevant AI skills to key topics in the field, including neural networks, generative AI, AI security, intelligent image processing, reinforcement learning, automated reasoning, 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