DATSC-MS - Data Science

1. 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;

2. Linear algebra including basic matrix manipulation, dot and cross products, inverse matrices, eigenvalues, representing problems as matrices, and solving small systems of linear equations;

3. Programming in a high-level language such as Python, Java, JavaScript, C++, C, Ruby, or SAS (2+ years). Applicants must be able to write working code from scratch;

4. 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,

5. Analytical thinking including the ability to translate real-world phenomena into quantitative representations and, conversely, the ability to interpret quantitative representations with practical explanations.

1. 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,

2. 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 email datascience@sps.cuny.edu.