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This fall, BU MET introduces the Master of Science in Applied Data Analytics<\/a>. The newest addition to MET\u2019s robust portfolio of analytics programs, the degree will help students develop key skills that will qualify them for the role of data scientist. \u201cManagers need to know how to handle the explosion of information extracted from very large data sets,\u201d says Department of Computer Science Chair Anatoly Temkin<\/a>. Through a curriculum that emphasizes the practical use of modeling and machine learning to make smarter organizational decisions, the program is to be offered online or evenings on campus and can be completed in as few as 16 months.<\/p>\n <\/p>\n Boston University\u2019s Metropolitan College Announces August 2019, Boston<\/strong>\u2014The Boston University Metropolitan College (MET) Department of Computer Science announces its new Master of Science in Applied Data Analytics (MSADA)<\/a> program. Launching in fall of 2019, the eight-course (32 credits) degree program will position graduates to meet the growing need for professional analytics talent across industry. \u201cManagers need to know how to handle the explosion of information extracted from very large data sets,\u201d says Dr. Anatoly Temkin, chair of Computer Science. Through a curriculum that develops a substantive foundation in the field of data analytics and emphasizes the practical use of modeling and machine learning to make smarter organizational decisions, the program is to be available online or evenings on campus and can be finished in as few as 16 months.<\/p>\n The new master\u2019s degree is a hands-on program designed for professionals with computer science or engineering backgrounds, or similar experience, who wish to gain an in-depth understanding of Python, R, and the application of concepts and techniques for organizing, cleaning, analyzing, and visualizing large amounts of data. With an emphasis on the computer science elements of data analysis and focus on developing applied knowledge and ability, degree students will gain a working understanding of the latest industry tools and approaches to databases.<\/p>\n Project-driven course work across the program will give students the chance to graduate with a significant portfolio of analytics-based output, priming them to be worthy candidates to enter the field of data science\u2014a realm expected to have nearly 364,000 new job postings nationally by 2020, for a total of more than 2,700,000, according to The Quant Crunch, a report from IBM, the Business-Higher Education Forum, and Burning Glass.<\/p>\n MSADA students will gain extensive exposure to database systems including Oracle, SQL Server, and PostgreSQL; data mining tools like Weka; data visualization tools and packages that include Tableau, ggplot2, Ploty, Matplotlib, and Seaborn; Python packages; R packages; and cloud services such as Amazon AWS, Google Cloud, and Mass Open Cloud. In addition to the program\u2019s six core courses, students may tailor their studies through two relevant electives, which can include advanced databases, data warehouse design and implementation, and big data analytics.<\/p>\n Established by Dr. Suresh Kalathur, director of analytics programs, and Dr. Temkin, the MSADA is the latest addition to MET\u2019s extensive portfolio of analytics-focused programs, which include data analytics concentrations in both the MS in Computer Science<\/a> and the MS in Computer Information Systems<\/a>, as well as the MS in Applied Business Analytics<\/a> offered through the Department of Administrative Sciences. \u201cThe MSADA aligns with BU MET\u2019s strategic objective to integrate robust analytics curricula throughout our programs and departments,\u201d says Dean Tanya Zlateva, \u201cand compliments Boston University\u2019s over-arching Data Science Initiative.\u201d The first of its kind at BU, the MET Computer Science department has taken a leadership role in innovation in the field for the more than three decades since its inception.<\/p>\nPress Release<\/h2>\n
\nNew Master\u2019s Degree in Applied Data Analytics<\/strong><\/p>\n