Master of Science (MSc) in Data Science & AI
Total Credits: 30-36 credits
Core Courses
DSAI 5101 — Advanced Data Science (3)
DSAI 5201 — Statistics & Probability (3)
DSAI 5301 — Machine Learning (3)
DSAI 5401 — Deep Learning & Neural Networks (3)
DSAI 5501 — Big Data & Cloud Computing (3)
DSAI 5601 — Ethics & Responsible AI (2)
DSAI 5901 — Capstone / Thesis (4)
Electives (choose 6-9 credits)
Natural Language Processing
Computer Vision
Reinforcement Learning
Data Engineering & Pipelines
Privacy & Data Security
Explainability & Interpretability
Advanced Topics in AI
Thesis / Capstone
Practical project or original research culminating in a thesis report and presentation
Master of Science in Data Science & Artificial Intelligence
Total Credits Needed: 30-36 credits (varies by institution)
Core Courses (15 credits)
1. DSAI 5101 - Introduction to Data Science — 3 credits
Prerequisites: None
Description: Foundations of data science, data lifecycle, and basic analysis.
2. DSAI 5201 - Statistics for Data Science — 3 credits
Prerequisites: None
Description: Descriptive and inferential statistics, probability, and hypothesis testing.
3. DSAI 5301 - Machine Learning — 3 credits
Prerequisites: DSAI 5201, DSAI 5101
Description: Supervised/unsupervised learning, model evaluation.
4. DSAI 5401 - Big Data Systems — 3 credits
Prerequisites: DSAI 5301 or equivalent
Description: Distributed computing frameworks, handling large datasets.
5. DSAI 5501 - Data Ethics & Privacy — 2 credits
Prerequisites: None
Description: Ethical considerations, bias, fairness, and privacy issues.
Electives (select courses totaling 6-9 credits)
- Deep Learning & Neural Networks
- Natural Language Processing
- Data Visualization & Dashboard Design
- Time Series Analysis
- Reinforcement Learning
- Data Engineering & Cloud Platforms
- AI in Business & Society
- Privacy-Preserving Data Mining
Thesis / Capstone Project (3-6 credits)
- DSAI 5999 - Thesis / Capstone Project — 3-6 credits
Prerequisites: Completion of core courses, proposal approval
Description: Conduct original research or a practical project demonstrating mastery in data science.
Note: We may require you to take a final comprehensive exam or complete additional coursework in addition to the thesis.