COE 4213564 - Introduction to Artificial Intelligence
Spring 2022
Course Info:
The objective of this course is to introduce and teach the fundementals of problems, theories, algorithms and applications of Artificial Intelligence (AI). AI is a very fast-growning field that focuses on building intelligent systems that will have a great impact on every aera of industry, economy, and social life. The topics include definition and history of AI, problem solving via search, game playing, knowledge representation, propositional logic, first-order predicate logic, logical and probabilistic reasoning, planning, uncertain knowledge and reasoning, machine learning (popular machine learning algorithms, deep learning, reinforcement learning, and genetic algorithms), natural language processing, deep learning for natural language processing, computer vision and robotics.
Prerequisite Courses
Data Structures
Required Text(s)
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Artificial Intelligence: A Modern Approach, 4th Edition, by Stuart Russell and Peter Norvig.(html).
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Recomended Text(s)
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Meeting Times:
- Tuesday 11:00 - 14:50, Location: C-317Labs:
- Lab : No labsTentative Grading:
| Evaluation Tool (*) | Weight in % |
|---|---|
| Assignments, Presentations and Projects |
30 |
| In-term Exams - 1 Midterm |
30 |
| Final | 40 |
Tentative Course Outline:
| WEEK | TOPIC(S) |
|---|---|
| 1 | Introduction and Intelligent Agents |
| 2 | Problem Solving by Searching |
| 3 | Adversarial Search and Games |
| 4 | Constraint Satisfaction Problems |
| 5 | Logical Agents |
| 6 | First-Order Logic Inference in First-Order Logic |
| 7 | Knowledge Representation Automated Planning |
| 8 | Uncertain knowledge and reasoning |
| 9 | Exam Week |
| 10 | Probabilistic Programming Making Simple Decisions Making Complex Decisions |
| 11 | Machine Learning |
| 12 | Deep Learning Reinforcement Learning |
| 13 | Natural Language Processing Deep Learning for Natural Language Processing .. |
| 14 | Computer Vision Robotics |
| 15 | Review |