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Master of Science in Data Science
The MS in Data Science (previously MS in Data Analytics) online degree program helps students earn the credentials and acquire the skills needed to enter or advance in the fast-growing field of data science. Ranked last year as one of the top Master’s in Data Science worldwide as well as one of the Best Value Online Big Data Programs, the MS in Data Science online degree program offers foundational knowledge and hands-on programming competencies, resulting in project-based work samples similar to that of a programming boot camp.
The program’s learning objectives and demanding, hands-on courses are designed around employer needs. Throughout their time in the program, students build portfolios of increasingly complex projects using popular programming languages such as R and Python, which mirror the current experience and demands of the IT workplace. Students build predictive and prescriptive models, practice giving presentations, and review each other’s work in a convenient online setting, ensuring that they are equipped with the expertise most valued in today’s marketplace. The MS in Data Science program culminates with a capstone project that represents highly sophisticated, but practical, solutions to address real world problems.
Additionally, the program’s faculty comprise committed and engaged technology practitioners who are experts in their fields. They invest time in building courses on the use of open source best-practice tools that satisfy high employer demands for quality programming and use of advanced techniques.
The MS in Data Science program prepares graduates for a variety of technical and managerial positions, such as data scientist, business intelligence analyst, knowledge, and informatics engineer, data analyst, data mining engineer, and data warehousing manager.
Applicants must possess a bachelor’s degree from an accredited institution, with a GPA of 3.0 or higher on a 4.0 scale. Applicants are required to write a personal statement, upload a resume, and provide two letters of recommendation. An individual interview may be necessary.
As an interdisciplinary field, we welcome applicants from diverse professional backgrounds. However, because the MS in Data Science is a highly quantitative and technical major as compared with MBA-like programs, acceptance requires applicants to demonstrate current skills in:
- Statistics and probability including descriptive statistics, skewness/kurtosis, histograms, statistical error, correlation, single variable linear regression analysis, significance testing, probability distributions, and basic probability modeling;
- Linear algebra including basic matrix manipulation, dot and cross products, inverse matrices, eigenvalues, representing problems as matrices, and solving small systems of linear equations;
- Relational databases including connecting to and manipulating data, working with tables, joins, basic relational algebra, and SQL queries. Two or more years of experience with Microsoft Access can be substituted if the applicant is able to perform the same operations without using Access’s graphical interface; and,
- Analytical thinking including the ability to translate real-world phenomena into quantitative representations and, conversely, the ability to interpret quantitative representations with practical explanations.
Skills in these areas will be assessed in two ways:
- Completion of credit-bearing coursework with a grade of B or better from an accredited college or university OR 2+ years of relevant experience on a resume; and,
- Completion of a mandatory challenge exam that will assess current skill and knowledge in these areas. If you lack the skills required for admission to the program and/or are unable to answer the questions found in the challenge exam, please email DataScience@sps.cuny.edu for recommendations on how to pick up the necessary skill sets.
If you have completed credit-bearing courses in the above areas or have used these skills at work but are no longer proficient, we offer three bridge courses: R Programming, SQL, and Data Science Math. These bridge courses are intended to refresh knowledge and skills, but are not for individuals who are learning these topics for the first time.
For questions, please contact Rokshana Ali at email@example.com or (646) 344-7302.
Applications for Spring 2019 are due by December 13, 2018Apply Now