Introduction to Artificial Intelligence is a three-credit undergraduate course emphasizing the building of agents, environments, and systems that can be considered as acting intelligently. In particular, you will learn about the methods and tools that will allow you to build complete systems that can interact intelligently with their environment by learning and reasoning about the world.
There are three primary objectives for the course: To provide a broad survey of AI; To develop a deeper understanding of several major topics in AI; To develop the design and programming skills that will help you to build intelligent artifacts.
In practice, you should develop enough basic skills and background that you can pursue any desire you have to learn more about specific areas in IS, whether those areas are planning, knowledge representation, machine learning, vision, robotics or whatever. In particular, this class provides a useful foundation for a number of courses involving intelligence systems, including Machine Learning (CS4641), Knowledge-Based AI (CS4634), Computer Vision (CS4495), Robotics and Perception (CS4632), Natural Language Understanding (CS4650) and Game AI (CS4731).
- Intro to AI
- Agents
- Uniformed Search
- Informed Search
- Markov decision processes
- Reasoning with uncertainty
- Probabilistic reasoning over time
- Intro to machine learning
- Decision trees
- Neural networks
- Advanced neural networks
- Societal implications
- Project 01 - Search in Pacman
- Project 02 - Reinforcement Learning
- Project 03 - Ghostbusters
- Project 04 - Neural Nets
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent