Machine Learning and Applications

Course Coordinator: Dr Jeff Au Yeung, BEng (Hons) HKUST, MPhil HKUST, PhD HKUST, SMIEEE, MIET, MHKCS

Course Developer: Kendrew Lau Chu-man, Consultant

This course aims to expose students to a broad overview of machine learning algorithms with a focus of applying these algorithms to solve real-world problems.

Advisory prerequisite(s)
You are advised to have already studied COMP S201 or COMP S258.

Aims
The course aims to:

• provide students with the fundamental concepts and basic algorithms of machine learning and data mining; and
• enable students to apply machine learning and data mining in creating software to solve real-world problems.

Contents
The course covers the following topics:

• Introduction to machine learning
• Essential Python programming and tools
• How machine learning and data mining work
• Supervised learning
• Unsupervised learning
• Deep learning
• Reinforcement learning

Learning Support
There will be tutorials and surgeries.

Assessment
There are four assignments and a final examination. Students are required to submit assignments through the Online Learning Environment (OLE).

Online Requirement
This course is supported by the Online Learning Environment (OLE). The most updated course material, course news and announcements are disseminated through the OLE. The use of the OLE is mandatory for this course.

Equipment
Students need access to a personal computer with Internet access. The minimum requirements are:

• Microsoft Windows 10 or above
• A quad-core processor
• 8 GB memory
• 50 GB free hard disk space

Set book(s)
There is no set book for this course.

Students with disabilities or special educational needs
The audio and visual components of this course may cause difficulties for students with hearing or vision impairments. You are encouraged to seek advice from the Course Coordinator before enrolling in this course.