PhD in Data Science & Artificial Intelligence

Total Credits Needed: 30-36 credits (excluding dissertation)

Core Courses (Research & Foundational Knowledge)

1. DSAI 7001 - Advanced Theoretical Foundations of Data Science and AI — 3 credits

• Prerequisites: Master’s degree in Data Science, AI, Computer Science, or related field

• Description: In-depth study of mathematical and theoretical principles underpinning AI and data science, including probability, statistics, information theory, and algorithm complexity.

2. DSAI 7101 - Research Methodologies & Scientific Communication — 3 credits

• Prerequisites: Graduate standing

• Description: Research design, experimental methods, scientific writing, ethics, and presentation skills.

3. DSAI 7201 - Seminar on Cutting-Edge Topics in AI & Data Science — 2 credits

• Prerequisites: Graduate standing

• Description: Critical review of recent advances, research papers, and emerging challenges in AI and data science.

Electives (Choose 6-9 credits based on research focus)

1. - Deep Learning & Neural Networks

2. - Natural Language Processing (NLP)

3. - Computer Vision and Image Analysis

4. - Reinforcement Learning & Autonomous Agents

5. - Big Data Infrastructure & Cloud Computing

6. - Data Ethics & Responsible AI

7. - Privacy-Preserving Machine Learning

8. - Explainability & Interpretability in AI

9. - Multi-modal Data Analysis

10. - Robotics & Autonomous Systems

(Electives are tailored to support the student’s research interests and dissertation topic)

Dissertation Research

- DSAI 7999 - Dissertation Research — 12 credits

• Prerequisites: Successful completion of coursework, qualifying exams, and research proposal approval

• Description: Conduct independent, original research contributing new knowledge to AI and data science, culminating in a dissertation and public defense.

Additional Requirements

1. - Qualifying Exams: Usually after coursework, to validate readiness for independent research

2. - Research Proposal: Must be approved before starting dissertation research

3. - Dissertation Defense: Final presentation and defense of research findings before a committee