Minor in Artificial Intelligence (AI)

Overview

The minor in Artificial Intelligence (AI) provides students with the fundamental knowledge and skills needed to pursue careers pertaining to AI technology, covering machine learning, deep learning, data analytics, natural language processing, and intelligent system design. The minor is open to students from diverse engineering fields and other disciplines. It is complementary to Computer, Mechatronics, Electrical, Industrial, and Mechanical Engineering. It also provides added value for students majoring in Civil Engineering, Chemical Engineering, and Petroleum Engineering, as well as Business, Economics, and Sciences. It provides hands-on experience with AI tools and techniques in different applications.

Program Objectives

Students who earn the Minor in AI will have the theoretical and practical foundation to achieve the following educational objectives within a few years of graduation:

1. Become knowledgeable and versed in the field of AI, spearheading innovative applications.
2. Apply AI techniques to address and solve different practical and real-world problems from diverse fields of study.
3. Tackle emerging challenges to advance AI and drive technological progress in an era defined by rapid digital evolution and growing AI dependency.
4. Highlight ethical and social implications of AI technologies, ensuring students understand the responsible use of AI.

Learning Outcomes

By the time of the completion of the minor, students are expected to:

• SO.1. Apply computational and engineering methods to design innovative, intelligent solutions to complex, real-world challenges.
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• SO.2. Recognize and evaluate emerging developments and trends in the multidisciplinary field of AI, spanning machine learning, deep learning, reinforcement learning, data analytics, and intelligent system design.

Minor Requirements

To obtain this minor, the student is required to complete 3 credits of core courses, 6 credits of general courses and 9 credits of elective courses. Up to 9 credits may count towards fulfilling the requirements and electives of the student’s main program of study. The student must achieve a minor GPA of at least 2.0 in the courses related to the Minor.

Minor Curriculum

• Core courses (3 credits)

   Choose one of the following courses:

1. COE211* Computer Programming (4 credits)
2. COE212 Engineering Programming (3 credits)
3. CSC243 Introduction to Object-Oriented Programming (3 credits)
4. BIF243 Introduction to Object-Oriented Programming (3 credits)
5. ITM201 Computer Programming (3 credits)

*: only 3 credits will count towards the minor

• General courses (6 credits)

Choose two of the following courses:

• LAS211 Prompting the Future with AI (3 credits)
• GNE336 Trustworthy and Secure AI (3 credits)
• CSC460 Artificial Intelligence (3 credits)
• CSC463 Introduction to Data Science (3 credits)
• COE546* Machine Learning (3 credits)
• CSC461* Introduction to Machine Learning (3 credits)

*: COE546 and CSC461 cannot be taken together
 

• Elective courses (9 credits)

Choose three of the following courses:

• COE550 Reinforcement Learning
• COE554 Computer Vision and Deep Learning (3 credits)
• COE548 Large Language Models (LLMs) (3 credits)
• COE543 Intelligent Data Processing and Applications (3 credits)
• COE544 Intelligent Engineering Algorithms (3 credits)
• COE549 Advanced Large Language Models (3 credits)
• COE547** Deep Learning (3 credits)
• CSC462** Fundamentals of Deep Learning (3 credits)
• CSC464** Deep Learning for Natural Language Processing (3 credits)

**: COE547, CSC462 and CSC464 cannot be taken together