Data Science & Engineering (DSE) Subplan Requirements
Degree Requirements
- Students enrolled in the Professional MS in Computer Science (MSCPS) program with the Data Science & Engineering (DSE) subplan must complete 30 credit hours of graduate coursework that align with the MSCPS degree requirements, including the requirements for the DSE subplan:
- 9 hours - Bin/Breadth courses
- You must earn a grade of ‘B’ or better to satisfy each of the three BIN/breadth course requirements.
- 6 hours - Project courses
- Students must complete both project courses from one project course sequence.
- Students must earn grades of ‘B’ or better in both courses.
- Students cannot count just one project course to the degree.
- 15 hours - Elective courses
- You may take up to two, approved, non-CS courses.
- Any non-Computer Science courses that can count towards a subplan will count against the two maximum allowable non-CS classes.
- DSE Subplan courses
- Must complete at least 12 credit hours of eligible DSE subplan courses with a grade of ‘B’ or better.
- Counting courses for the DSE subplan
- Students can satisfy subplan requirements by counting eligible BIN and/or Elective courses towards the DSE subplan requirements. This means:
- Students may count an eligible course towards BOTH a BIN/breadth requirement AND a DSE subplan requirement.
- If the student does not need to count an eligible course towards the breadth/bin requirement, the course can count towards BOTH an elective requirement AND a DSE subplan requirement.
- For example, if a student got a grade of ‘B’ or higher in CSCI 5214:
- …and still needed to complete their Bin 3 requirement - They could count CSCI 5214 as BOTH their Bin 3 course and as a DSE subplan course.
- …and already completed their Bin 3 requirement - they could count CSCI 5214 as BOTH an Elective course and as a DSE subplan course.
- Students can satisfy subplan requirements by counting eligible BIN and/or Elective courses towards the DSE subplan requirements. This means:
- 9 hours - Bin/Breadth courses
Data Science & Engineering (DSE) Subplan Course Options
- CSCI 5214 - Big Data Architecture
- CSCI 5253 - Datacenter Scale Computing
- CSCI 5254 - Convex Optimization
- CSCI 5352 - Network Analysis and Modeling
- CSCI 5434 - Probability for Computer Science
- CSCI 5502 - Data Mining
- CSCI 5576 - High-Performance Scientific Computing
- CSCI 5622 - Machine Learning
- CSCI 5654 - Linear Programming
- CSCI 5676 - Numerical Methods for Unconstrained Optimization
- CSCI 5722 - Computer Vision
- CSCI 5832 - Natural Language Processing
- CSCI 5922 - Neural Networks and Deep Learning
- CSCI 6502 - Big Data Analytics: Systems, Algorithms, and Applications
- ATLS 5214 - Big Data Architecture