B.ENG IN ARTIFICIAL
BS IN ARTIFICIAL INTELLIGENCE (AI)
Required Courses
- Academic Orientation for AI Students
- Design and Analysis of Algorithms
- Mathematics for AI
- Python Programming for Artificial Intelligence
- Introduction to Data Mining
- Introduction to Computer Vision
- Fundamentals of Artificial Intelligence
- Machine Learning
- Senior Project/Capstone for AI
Sample Elective Courses
- Exploring Artificial Intelligence
- Ethics in Artificial Intelligence
- Disciplinary-based English I
- Introduction to Natural Language Processing
- Introduction to Reinforcement Learning
- Machine Learning and Information Processing for Robotics
- Learning and Optimization for Artificial Intelligence
- Machine Learning with Big Data
- Introduction to Financial Engineering
- Operating Systems
- Disciplinary-based English II
- Deep Learning in Visual Intelligence
- Introduction to Bayesian Networks
- Robotic Manipulation and Mobility
Program Learning Outcomes
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01Analyze AI and computing problems in different areas of science, technology, and society, and apply AI principles to produce solutions.
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02Design, implement, and evaluate algorithms to solve AI models.
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03Communicate effectively in a variety of professional contexts, including both lay and expert audiences.
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04Recognize professional responsibilities and make informed and independent judgments through solving practical AI models based on legal and ethical principles.
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05Function effectively as a team member or as a team leader in activities appropriate to the program’s discipline.
ENG
General Information
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Credit structure:
PhD: 21 credits
BSc: 118 credits
