ARTIFICIAL
PHD IN ARTIFICIAL INTELLIGENCE (AI)
Required Courses
- 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
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01Demonstrate thorough knowledge of the literature and a comprehensive understanding of scientific methods and techniques relevant to AI.
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02Demonstrate practical skills in building AI systems.
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03Critically apply theories, methodologies, and knowledge to address fundamental questions in AI.
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04Independently pursue research or innovation of significance in AI applications.
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05Demonstrate skills in oral and written communication sufficient for a professional career.
PHD
General Information
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Credit structure:
PhD: 21 credits
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Normative Program Duration:
PhD:
Full-time: 3 years (those with a relevant research master’s degree), 4 years (those without a relevant research master’s degree)
