Course Overview

Welcome to CSE005 , Artificial Intelligence (AI). You are joining a global learning community dedicated to helping you learn and thrive in the AI era.

📺 Watch this welcome video from your instructor.

Course Description

Artificial Intelligence (AI) aims to teach students the techniques for building computer systems that exhibit intelligent behavior. AI is one of the most consequential applications of computer science, and is helping to solve complex real-world problems, from self-driving cars to facial recognition. This course will teach students the theory and techniques of AI, so that they understand how AI methods work under a variety of conditions.

The course begins with an exploration of the historical development of AI, and helps students understand the key problems that are studied and the key ideas that have emerged from research. Then, students learn a set of methods that cover: problem solving, search algorithms, knowledge representation and reasoning, natural language understanding, and computer vision. Throughout the course, as they apply technical methods, students will also examine pressing ethical concerns that are resulting from AI, including privacy and surveillance, transparency, bias, and more.

Course assignments will consist of short programming exercises and discussion-oriented readings. The course culminates in a final group project and accompanying paper that allows students to apply concepts to a problem of personal interest.

Topics

  • Intelligent Agents
  • Search strategies
  • Game Playing
  • Knowledge and Reasoning
  • Natural Language Processing
  • Computer Vision
  • Ethics and safety

How the course works

There are multiple ways you'll learn in this course:

  • Read and engage with the materials on this site
  • Attend live class and complete the activities in class
  • Answer practice exercises to try out the concepts
  • Complete assignments and projects to demonstrate what you have learned

Active engagement is necessary for success in the course! You should try to write lots of programs, so that you can explore the concepts in a variety of ways.

You are encouraged to seek out additional practice problems outside of the practice problems included in the course.

Learning Outcomes

By the end of the course, students will be able to:

  • Demonstrate understanding of the foundation and history of AI
  • Explain basic knowledge representation, problem solving, inference, and learning methods of AI
  • Develop intelligent systems to solve real-world problems by selecting and applying appropriate algorithms
  • Explain the capabilities and limitations of various AI algorithms and techniques
  • Participate meaningfully in discussions of AI, including its current scope and limitations, and societal implications

Instructor

Please contact on Discord first with questions about the course.

Live Class Time

Note: all times are shown in GMT.

  • Wednesday, 15:00 - 16:30 GMT

Office Hours

  • Tuesday, 15:00 - 16:30 GMT

Core Reading List

  • Norvig P., Russell S. (2020). Artificial Intelligence: A Modern Approach. Pearson, 4th e. (Chapters 1-12, 23, 24, 25,27)

Supplemental Reading List

  • Zhang A, Lipton Zn, Li M, Smola A. (2021) Dive into Deep Learning