This course gives lectures and practical exercises on machine learning algorithms and to cultivate the ability to implement the algorithm with actual data by using Python code. Specifically, this course introduces the basics of machine learning, unsupervised learning, and supervised learning. In addition, deep learning algorithms are also covered.
Students will acquire the following skills by taking this course.
1) Be able to understand the basic concepts of machine learning algorithms and Python programing
2) Be able to select and implement machine learning methods for your own purposes
Machine learning, programming, Python, algorithm
|✔ Specialist skills||Intercultural skills||Communication skills||Critical thinking skills||✔ Practical and/or problem-solving skills|
Brief lectures are given in the first half of each class. Then, students will tackle practical exercises on the given contents.
|Course schedule||Required learning|
|Class 1||Python installation, basics of Python code||Preparing a Python development environment for basic programming.|
|Class 2||Basics of machine learning, unsupervised learing and thier practical exercises||Understanding the basics of machine learning and the procedures for unsupervised learning.|
|Class 3||Practical Exercise||Practical exercise on unsupervised learning based on actual data.|
|Class 4||Basics of supervised learning and its exercise||Understanding the basics of supervised learning.|
|Class 5||Practical Exercise||Practical exercise on supervised learning based on actual data.|
|Class 6||Basics of deep learning and its exercise||Understanding the basics of deep learning.|
|Class 7||Practical exercise||Practical exercise on deep learning based on actual data.|
Course materials will be distributed at the class
Assessed by the three exercises.