MS with Concentration in Data Science and Engineering
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 concentration 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 distributed data management, basics of probability, visualization, statistical learning, scalability, and optimization.
Course Requirements:
To qualify for the Data Science and Engineering Specialization in the MS in Computer Science Program, student must take at least 4 of the following courses:
- CSE 512: Machine Learning
- CSE 519: Data Science Fundamentals
- CSE 537: Artificial Intelligence
- CSE 544: Probability and Statistics for Data Scientists
- CSE 545: Big Data Analytics
- CSE 548: Analysis of Algorithms
- CSE 564: Visualization
No other courses will be accepted for the 4 course requirement beyond the 7 above.
In addition, the student must complete an advanced project sequence (523/524 or equivalent) or an MS thesis (599 or equivalent). Where applicable, these courses can be taken as part of the MS breadth requirement.
MS CS Students satisfying the above requirements will automatically have the concentration designation added to their transcript upon graduation. No action beyond fulfilling the requirements is necessary.
Questions about this concentration may be sent to Director for Data Science Concentration, Prof. Andrew Schwartz, at andrew.schwartz@cs.stonybrook.edu.