Online Data Analytics Graduate Certificate
The rapid pace at which digital data is being generated has resulted in very large amounts of data, usually referred to as “Big Data,” which require new techniques for processing and analysis. Data analytics is needed in nearly every industry to guide decision-making processes through the collection and analysis of available data—yet, according to a McKinsey Global Institute assessment, the United States alone faces a shortage of 140,000 to 190,000 personnel with the requisite deep analytical skills.
The new Graduate Certificate in Data Analytics will provide professionals with the skills required to compete for data analysis jobs amid rising global demand. The certificate program will explore the intricacies of data analytics and expose students to various topics related to data processing, analysis, and visualization. Along with probability theory and statistical analysis methods and tools, students will learn how to generate relevant visual presentations of data and will examine concepts and techniques for data mining, text mining, and web mining. Individuals who complete this program will have a solid knowledge of data analytics practices accompanied by exposure to the methods and tools for data mining and knowledge discovery.
Students who complete the Graduate Certificate in Data Analytics will be able to demonstrate:
- Familiarity with applied probability and statistics, and their relevance in day-to-day data analysis
- The ability to explore the various data visualization techniques and their applications using real-world data sets
- An understanding of web analytics and metrics, procure and process unstructured text, and delve into the hidden patterns
- Skills in facilitating knowledge discovery using data mining techniques over vast amounts of data
Why Choose BU’s Graduate Certificate in Data Analytics?
- Four-course certificate program comprises courses shared by the MS in Computer Information Systems, ranked #6 among the nation’s Best Online Graduate Computer Information Technology Programs (U.S. News & World Report 2018).
- Students benefit from a supportive online network, with courses developed and taught by PhD-level full-time faculty and professionals with hands-on expertise in the industry.
- Small course sections ensure that students get the attention they need, while case studies and real-world projects ensure that they gain in-depth, practical experience with the latest technologies.
Computer and Information Systems Managers
12% increase in jobs through 2026
$139,220 median annual pay in 2017
Computer and Information Research Scientists
19% increase in jobs through 2026
$114,520 median annual pay in 2017
Computer Systems Analysts
9% increase in jobs through 2026
$88,270 median annual pay in 2017
11% increase in jobs through 2026
$87,020 median annual pay in 2017
Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2017-18 Edition
Best Technology Jobs, 2018 U.S. News & World Report
- #1 Software Developer
- #2 Information Security Analyst
- #3 IT Manager
- #4 Computer Systems Analyst
- #5 Computer Network Architect
- #6 Computer Systems Administrator
- #7 Database Administrator
- #8 Web Developer
- #9 Computer Support Specialist
- #10 Computer Programmer
By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.
McKinsey & Company
Big data: The Next Frontier for Innovation, Competition, and Productivity, 2011
Boston University Metropolitan College (MET) offers competitive tuition rates that meet the needs of part-time students seeking an affordable education. These rates are substantially lower than those of the traditional, full-time residential programs yet provide access to the same high-quality BU education. To learn more about current tuition rates, visit the MET website.
Comprehensive financial assistance services are available at MET, including graduate assistantships (up to $4,200 per semester), scholarships, graduate loans, and payment plans. There is no cost to apply for financial assistance, and you may qualify for a student loan regardless of your income. Learn more.
Boston University’s Graduate Certificate in Data Analytics consists of four required online courses (16 credits).
(Four courses/16 credits)
METCS544 Foundations of Analytics with R
The goal of this course is to provide students with the mathematical and practical background required in the field of data analytics. Starting with an introduction to probability and statistics, the R tool is introduced for statistical computing and graphics. Different types of data are investigated along with data summarization techniques and plotting. Data populations using discrete, continuous, and multivariate distributions are explored. Errors during measurements and computations are analyzed in the course. Confidence intervals and hypothesis testing topics are also examined. The concepts covered in the course are demonstrated using R. Laboratory Course. Prereq: MET CS546 and (MET CS520 or MET CS521), or equivalent knowledge, or instructor's consent. [4 credits]
METCS555 Data Analysis and Visualization with R
This course provides an overview of the statistical tools most commonly used to process, analyze, and visualize data. Topics include simple linear regression, multiple regression, logistic regression, analysis of variance, and survival analysis. These topics are explored using the statistical package R, with a focus on understanding how to use and interpret output from this software as well as how to visualize 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. Recommended Prerequisite: MET CS 544 or equivalent knowledge, or instructor's consent. [4 credits]
METCS688 Web Analytics and Mining
The Web Analytics and Mining course covers the areas of web analytics, text mining, web mining, and practical application domains. The web analytics part of the course studies the metrics of web sites, their content, user behavior, and reporting. Google analytics tool is used for collection of web site data and doing the analysis. The text mining module covers the analysis of text including content extraction, string matching, clustering, classification, and recommendation systems. The web mining module studies how web crawlers process and index the content of web sites, how search works, and how results are ranked. Application areas mining the social web and game metrics will be extensively investigated. Laboratory Course. Prerequisites: MET CS 544, or MET CS 555 or equivalent knowledge, or instructor's consent. [4 credits]
METCS699 Data Mining
The goal of this course is to study basic concepts and techniques of data mining. The topics include data preparation, classification, performance evaluation, association rule mining, and clustering. We will discuss basic data mining algorithms in the class and students will practice data mining techniques using data mining software. Students will use Weka and SQL Server or Oracle. Prereq: MS CS Prerequisites: MET CS 579; or instructor's consent. MS CIS Prerequisites: MET CS 669 and MET CS 546; or instructor's consent. [4 credits]
Admission & Prerequisite Information
Applicants to the program are required to have a bachelor’s degree from a regionally accredited institution, in addition to the equivalent of MET CS 546. Some courses may have additional prerequisites.
METCS546 Quantitative Methods for Information Systems
The goal of this course is to provide Computer Information Systems students with the mathematical fundamentals required for successful quantitative analysis of problems in the field of business computing. The first part of the course introduces the mathematical prerequisites for understanding probability and statistics. Topics include combinatorial mathematics, functions, and the fundamentals of differentiation and integration. The second part of the course concentrates on the study of elementary probability theory, discrete and continuous distributions. Prereq: Academic background that includes the material covered in a standard course on college algebra or instructor's consent. [4 credits]
Assistant Professor, Computer Science; Director, Analytics
PhD, Brandeis University; MS, Indian Institute of Technology; BS, Regional Engineering College (Warangal, India)
Jae Young Lee
Assistant Professor, Computer Science; Coordinator, Databases
PhD, MS, University of Texas at Arlington; BS, Seoul National University (Korea)
To learn more or to contact an enrollment advisor before you get started, request information using the button below and tell us a little about yourself. Someone will be in touch to answer any questions you may have about the program and detail the next steps in earning your degree. You can also start your application or register for a course at Metropolitan College.