Imagine starting your day by checking your email, and without any effort, those annoying spam messages have already been filtered out. Or maybe you uploaded a group photo on social media, and the app instantly recognized your friends for tagging. Even the face recognition feature in your mobile phone that unlocks with just a glance—these are all powered by Supervised Learning. Supervised learning is like teaching AI by example. By feeding it labeled data, it learns to make predictions and decisions based on what it has seen before. Whether you're aiming to understand AI or build smarter business tools, mastering supervised learning is your gateway to innovation!

What you will learn:
- Linear Model
- Support Vector Machine
- Generalization
- Deep Learning
- Advanced topics such as Feature Engineering vs. Deep Features
- Multimodal Learning
- GAN

Prerequisites:
- This course is designed for everyone. No prior knowledge is required.

Recommended prior course:
- Computational Mathematics: Discrete Mathematics
- Computational Mathematics: Probability
- Computational Mathematics: Linear Algebra
- Applications of Artificial Intelligence: Theories and Innovations
- Basic Programming with Python for Artificial Intelligence
- Advanced Programming with Python Libraries for Artificial

Course type:
This is a core course (C) in the Master of Engineering program in Artificial Intelligence and Internet of Things (International Program) offered by Thammasat University and SkillLane.

Grading Criteria:
This course consists of 1) Quizzes, which account for 60% of the grade, 2) Final Exam, which accounts for 40% of the grade, Grades will be assigned based on the following scheme:

A 90-100
A- 85-89.99
B+ 80-84.99
B 75-79.99
B- 70-74.99
C+ 65-69.99
C 60-64.99
D 50-59.99
F 0-49.99

Instructor Background:
Dr. Sanparith Marukatat
Currently, Dr. Sanparith is a head of Image Processing and Understanding Team, National Electronics and Computer Technology Center (NECTEC). He has academic expertise in various fields including Computer Vision, Machine Learning, Information Retrieval, Image Processing, Signal Processing, and Speech/Pattern Recognition.

Dr. Sanparith completed his Bachelor’s degree in Computer Science, Franche-Comte University, Master’s degree in Computer Science, Franche-Comte University, and Ph.D. in Computer Science, The Paris 6 University.