INT-1903 Introduction to Artificial Intelligence and Machine Learning

In this course, students learn the fundamentals of artificial intelligence (AI) and machine learning (ML). Building upon their basic Python skills, students delve into the core concepts of AI, exploring the nature of intelligent agents and various agent architectures. They gain insight into problem-solving through search algorithms and constraint-based reasoning while developing proficiency in logical reasoning and knowledge representation. Additionally, the course introduces students to essential ML techniques, including feed-forward neural networks, probabilistic reasoning, and planning methods. Through a mix of theory and hands-on learning, students also explore game theory and minimax strategies, culminating in an understanding of reinforcement learning and probabilistic planning.

Prerequisite(s): INT-1111 .

Course Outcomes

1. Identify the main ideas behind artificial intelligence and machine learning, including different types of smart computer programs.
2. Compare and contrast different ways to represent information and solve problems in AI.
3. Write basic Python programming code to solve problems with search and rules in AI.
4. Create basic machine learning programs, such as simple computer brains.
5. Use prompt engineering for AI generated calculations of numbers and probability.
6. Explain how computer programs  learn and make plans based on experiences.