人工智慧
Artificial Intelligence
| 節 | 週四 |
|---|---|
6 14:20–15:10 | 人工智慧 EDB27（光復） 3 節連堂 |
7 15:30–16:20 | |
8 16:30–17:20 |
* 根據陽明交大上課時間表所列
The objective of this course is to learn the theory and practice of artificial intelligence (AI). The first part of the course provides a broad introduction to the fundamental concepts of AI. Topics may include reasoning and control, knowledge representation, and machine learning. The second part of the course is a hands-on lab co-taught with industry professionals from Deep Force to learn the best practices of implementing AI algorithms on smartphones and other edge devices.
There are no formal pre-requisites for the course, but students should have previous programming experience in Python. Students are welcomed to contact the instructor if they are unsure whether their backgrounds are suitable for the course.
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Homeworks 40%, midterm presentation 20%, final demonstration 40%
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| 週次 | 主題 |
|---|---|
| 第 1 週 | Overview of Artificial Intelligence (AI) What is artificial intelligence? Artificial Agents 02/21 |
| 第 2 週 | Peace Memorial Day 02/28 |
| 第 3 週 | Searching for Solutions Problem Solving as Search Searching Algorithms and Optimization A Python Tutorial Homework #1 03/07 |
| 第 4 週 | Supervised Machine Learning Basic Models for Supervised Learning Neural Networks and Deep Learning A Tutorial on Deep Learning with Tensorflow Homework #2 03/14 |
| 第 5 週 | Learning with Uncertainty Probabilistic Learning Learning Belief Networks 03/21 |
| 第 6 週 | Learning to Act Reinforcement Learning Exploration and Exploitation Homework #3 03/28 |
| 第 7 週 | Children's Day 04/04 |
| 第 8 週 | Reasoning with Constraints Constraint Satisfaction Problems (CSPs) Solving CSPs Using Search 04/11 |
| 第 9 週 | AI in Practice Part-I (by Deep Force & Qualcomm): A hands-on lab co-taught with industry professionals from Deep Force to learn the best practices of implementing AI algorithms on smartphones and other edge devices 04/18 |
| 第 10 週 | AI in Practice Part-I (by Deep Force & Qualcomm): A hands-on lab co-taught with industry professionals from Deep Force to learn the best practices of implementing AI algorithms on smartphones and other edge devices 04/25 |
| 第 11 週 | Midterm Presentation 05/02 |
| 第 12 週 | Midterm Presentation 05/09 |
| 第 13 週 | Reasoning with Uncertainty Probabilistic Inference Sequential Probability Models 05/16 |
| 第 14 週 | Relational Planning and Learning Planning with Individuals and Relations Relational Learning Homework #4 05/23 |
| 第 15 週 | Retrospect and Prospect Social Consequences Ethical Consequences 05/30 |
| 第 16 週 | AI in Practice Part-II (by Qualcomm): A hands-on lab co-taught with industry professionals from Deep Force to learn the best practices of implementing AI algorithms on smartphones and other edge devices 06/06 |
| 第 17 週 | AI in Practice Part-II (by Qualcomm): A hands-on lab co-taught with industry professionals from Deep Force to learn the best practices of implementing AI algorithms on smartphones and other edge devices 06/13 |
| 第 18 週 | *** (No course in this week. The course project demonstration is rescheduled to the next week) 06/20 |
| 第 19 週 | Course Project Demonstration 06/27 |
1. David L. Poole and Alan K. Mackworth, “Artificial Intelligence: Foundations of Computational Agents, 2nd Edition” Cambridge University Press, 2017. 2. Stuart J. Russell and Peter Norvig, “Artificial Intelligence: A Modern Approach, Third Edition,” Pearson Education, 2015. 3. George F. Luger, “Artificial Intelligence: Structures and Strategies for Complex Problem Solving, Sixth Ediction,” Pearson Education, 2009. 4. Instructor’s complementary material
- 地點
- By appointment
- 時間
- By appointment
- 聯絡方式
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