Artificial Intelligence Programming with Python

Serial Number
47582
Course Number
IMPS1004
Course Identifier
H41 10040
Class 01
3 Credits
A6
No Target Students
- No Target Students
CHEN, YAN-BIN
- View Courses Offered by Instructor
- COMMON GENERAL EDUCATION CENTER Master Program in Statistics of National Taiwan University
- yanbin@ntu.edu.tw
- Room 212, Chee-Chun Leung Cosmology Hall (次震宇宙館 212室)
- 02-33664688
- Website
  https://sites.google.com/view/yan-bin/home
- Yan-Bin Chen, PhD Assistant Professor Dept: Master Program in Statistics, Center for General Education
Wed 7, 8, 9
綜302
Type 2
Students can add courses online with the given permission number by the class instructor
50 Student Quota
NTU 46 + non-NTU 4
No Specialization Program
English
NTU COOL

Notes
The course is conducted in English。For non-EECS college students.。A6:Mathematics, Digital Competence, and Quantitative Analysis
NTU Enrollment StatusNTU students only. Updated every five minutes during the course selection period.
Enrolled
0/46
Other Depts
0/0
Remaining
0
Registered
0
Course Description
*** Notice *** Kindly notice that there is no need to send me an email for course enrollment. If you would like to take the course but were unable to successfully enroll, please come to class in the first week. We may deliver the authorization codes. The unsuccessful enrollment status will be announced after the preliminary course selection on January 17th. == Spring 2025 == The course is a practical programming class focused on artificial intelligence (AI) examples. Students are taught introductory Python language at the beginning, engage in hands-on programming in class, and implement AI examples in the final month of the course. If you are an Electrical Engineering or Computer Science (EECS) student or already have experience with Python programming, you’re most likely to be bored in this course, as it is specifically designed for non-EECS beginners. The course covers basic to advanced concepts of the Python programming language. The examples and exercises provided in the course primarily emphasize AI applications. Finally, students will use Python to implement the final project, which contains programming tasks (with hints, if necessary), and present their work. The course is taught in English, but bilingual Q&A sessions are acceptable. Teaching methods in each week: 70 mins: Lecture. 70 mins: Students engage in hands-on exercises and teamwork. You may use AI tools to assist you with the exercises. 10 mins: Conclusion of hands-on exercises and fundamental knowledge.
Course Objective
(1)Students are expected to have hands-on programming experience in the Python language. (2)By the end of the curriculum, students will be able to showcase their artificial intelligence programs or data analysis developed in Python through their final projects.
Course Requirement
The students should take along with their laptops in the class session.
Expected weekly study hours before and/or after class
2 hours
Office Hour
*This office hour requires an appointment
Designated Reading
Month 1,2: Book 1 Chapter 2,3,4,5 Month 2,3: Book 1 Chapter 6,7,8,9 Month 3,4: Book 2 Chapter 1,2,4
References
Book 1: Python for Data Analysis, 3E --- Data Wrangling with Pandas, NumPy, and Jupyter, 2022 By Wes McKinney Book 2: Artificial Intelligence with Python, 2017 By Prateek Joshi Online reading: Python Tutorial website. (https://www.tutorialspoint.com/python/)
Grading
50%
In class
Exercise in class session
50%
Final
Final project and presentation

Adjustment methods for students

Adjustment Method	Description
A3	提供學生彈性出席課程方式 Provide students with flexible ways of attending courses
B6	學生與授課老師協議改以其他形式呈現 Mutual agreement to present in other ways between students and instructors
C2	書面(口頭)報告取代考試 Written (oral) reports replace exams
D1	由師生雙方議定 Negotiated by both teachers and students

Make-up Class Information

Course Schedule

2/19Week 1	2/19	Introduction
2/26Week 2	2/26	[Part 1: Basic Python for Beginners] Introduction to Python and Environment Setup
3/05Week 3	3/05	Python Syntax
3/12Week 4	3/12	Python Syntax
3/19Week 5	3/19	Data Types
3/26Week 6	3/26	If-else, Loops, and File Read/Write
4/02Week 7	4/02	Pandas
4/09Week 8	4/09	Plot and Visualization
4/16Week 9	4/16	Handling of Missing Data in Pandas
4/23Week 10	4/23	Data Wrangling in Pandas: Sort, Merge, and Concatenate
4/30Week 11	4/30	[Part 2: AI Programming] Artificial Intelligence: Machine Learning
5/07Week 12	5/07	Artificial Intelligence: Deep Learning (ex:CNN)
5/14Week 13	5/14	Artificial Intelligence: Clustering (ex: K-Means)
5/21Week 14	5/21	Final Project Presentation I
5/28Week 15	5/28	Final Project Presentation II
6/04Week 16	6/04	Drop-In Discussion Session: Special Issues for the Python Programming

Artificial Intelligence Programming with Python - For Beginners