PHD IN ARTIFICIAL INTELLIGENCE (AI)
- Advanced Artificial Intelligence
- Machine Learning
- Statistical Machine Learning
Sample Elective Courses
- Bayesian Machine Learning
- Advanced Deep Learning
- Deep Reinforcement Learning
- Topics in Artificial Intelligence
- Topics in Machine Learning
- Parallel Programming
- Introduction to Bayesian Networks
- Natural Language Processing
- Statistical Learning Models for Text and Graph Data
- Perception and Information Processing for Robotics
- Computer Vision
- Introduction to Advanced Algorithmic Techniques
Program Learning Outcomes
01Demonstrate thorough knowledge of the literature and a comprehensive understanding of scientific methods and techniques relevant to AI.
02Demonstrate practical skills in building AI systems.
03Critically apply theories, methodologies, and knowledge to address fundamental questions in AI.
04Independently pursue research or innovation of significance in AI applications.
05Demonstrate skills in oral and written communication sufficient for a professional career.
PhD: 21 credits
Normative Program Duration:
Full-time: 3 years (those with a relevant research master’s degree), 4 years (those without a relevant research master’s degree)