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MS - Data Science and Engineering Specialization (MS-DSES)

Large-scale data generated by humans and machines is available everywhere. Acquiring the fundamental skills on how to 1) analyze and understand as well as 2) manage and process these large datasets is crucial in today's data- driven world for producing data products that solve real-world problems.

Through this specialization students learn the fundamental concepts in data science and develop a skill-set needed to become data scientists. Major areas covered through thought- provoking classes include scoping projects, data management, statistics basics, visualization, statistical learning, data mining, scalability, and optimization.

Course Requirements

To qualify for the DSES, the MS student must take at least 4 of the following courses: 

  1. CSE 519: Data Science Fundamentals
  2. CSE 544: Prob/Stat for Data Scientists
  3. CSE 545: Big Data Analytics
  4. CSE 512: Machine Learning
  5. CSE 537: Artificial Intelligence
  6. CSE 548: Analysis of Algorithms
  7. CSE 564: Visualization

In addition, the student must complete CSE 523, 524, or 599 (thesis). Where applicable, these courses can be taken as part of the MS breadth requirement.

With the approval of the DSES by the Graduate Council, any student satisfying the requirements of the specialization will receive a certification upon graduation.

Questions about this specialization may be sent to the MS-DSES Program Director, Andrew Schwartz, at andrew.schwartzatcs.stonybrook.edu (Andrew Schwartz).