NCHU Course Outline
Course Name (中) 人工智慧概論(1309)
(Eng.) Introduction to Artificial Intelligence
Offering Dept Bachelor Program in Intellectual Creativity Engineering
Course Type Required Credits 3 Teacher HUNG-CHUNG LI
Department Bachelor Program in Intellectual Creativity Engineering/Undergraduate Language English Semester 2024-FALL
Course Description The basic concepts of AI/machine learning algorithms would be introduced. Also, the students would understand how to implement those methods to solve the problems occurred in our daily life.

Self-directed Learning I: NVIDIA CEO Jensen Huang Keynote at COMPUTEX 2024 (https://reurl.cc/QRQnpO)
Self-directed Learning II: Andrew Ng: A Look At AI Agentic Workflows And Their Potential For Driving AI Progress (https://reurl.cc/Gj0ZxA)
Prerequisites
self-directed learning in the course Y
Relevance of Course Objectives and Core Learning Outcomes(%) Teaching and Assessment Methods for Course Objectives
Course Objectives Competency Indicators Ratio(%) Teaching Methods Assessment Methods
This course intends to introduce the concepts of Artificial Intelligence (AI) and its implementations. Also, each student should learn how to code and apply the algorithms so as to analyze the real-world problems.
topic Discussion/Production
Lecturing
Exercises
Discussion
Attendance
Assignment
Internship
Oral Presentation
Course Content and Homework/Schedule/Tests Schedule
Week Course Content
Week 1 Introduction to Artificial Intelligence (AI)
Week 2 Applications of AI and Its Problem Solving
Week 3 The Introduction of AI Procedure - I
Week 4 The Introduction of AI Procedure - II
Week 5 The Types of Machine Learning
Week 6 Machine Learning - Classification
Week 7 Machine Learning - Regression
Week 8 Project Proposal
Week 9 Machine Learning - Summary
Week 10 Introduction to Neural Network (NN) - I
Week 11 Introduction to Neural Network (NN) - II
Week 12 Implementation - I
Week 13 Implementation - II
Week 14 Implementation - III
Week 15 Data Visualization
Week 16 Final Presentation
Week 17 Self-directed Learning I - Participate in relevant lectures, workshops, or seminars using materials designated by the instructors.
Week 18 Self-directed Learning II - Participate in relevant lectures, workshops, or seminars using materials designated by the instructors.
Evaluation
Homework/Participation (40%), Project Proposal (20%), Final Presentation (30%), Self-directed Learning Report (10%)
Textbook & other References
Main Textbook: Handout
● Mohri, M., Rostamizadeh, A., & Talwalkar, A. (2018) Foundations of Machine Learning (2/e), MIT Press, ISBN: 9780262039406.
● Albon, Chris (2018) Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning, O’Reilly, ISBN: 9781491989388.

Teaching Aids & Teacher's Website
The course materials would be found at ilearn.
Office Hours
Wednesday 10:00-11:00 am or please contact the teacher to arrange a meeting time.
Sustainable Development Goals, SDGs
04.Quality Educationinclude experience courses:N
Please respect the intellectual property rights and use the materials legally.Please repsect gender equality.
Update Date, year/month/day:2024/07/01 20:49:09 Printed Date, year/month/day:2024 / 10 / 13
The second-hand book website:http://www.myub.com.tw/