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STEM1040 A Trilogy of Hands-on Machine Learning 親身體驗機器學習三部曲
Monday, January 01, 2001
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Artificial intelligence (AI) is all the rage these days. We are promised a future of more gadgets and services with AI-powered features such as intelligent chatbots, virtual assistants, and self-driving cars. The current AI boom was largely fuelled by breakthroughs in an area known as machine learning. It involves training computers to perform tasks based on examples rather than programming by a human. A branch of this approach called deep learning has made it more promising for solving perceptual problems such as image classification, face recognition, and natural language processing.

This course offers a hands-on exploration of machine learning through a trilogy approach: mathematical concepts, algorithms, and programming. We will begin with introducing what machine learning is, how it works, and what it can achieve. With a comprehensive treatment of the mathematics and theories involved, we will walk through typical implementations of artificial neural networks to see how the theories turn into practice. Then we will move on to teaching students to make some interesting AI applications (e.g. games) using the Python programming language and machine learning frameworks such as TensorFlow and Keras.




Organising units:
  • Department of Mathematics, Faculty of Science, CUHK
  • Department of Computer Science and Engineering, Faculty of Engineering, CUHK
  • Centre for Promoting Science Education, CUHK
Category: Category I – University Credit-Bearing
Learning outcomes: Upon completion of this course, students should be able to:
  1. Recognize the applications of chemistry in quantitative and qualitative chemical analysis;
  2. Understand the principles of various spectroscopic techniques for identification of molecular structures;
  3. Understand the principles of the spectroscopic and chromatographic techniques for composition analysis;
  4. Acquire hands-on experience in quantitative and qualitative chemical analysis with modern spectrometers.
Learning Activities:
  1. Lectures
  2. Exercise and Assignment
  3. Lab
Medium of Instruction: Cantonese supplemented with English
  1. Essays / Assignments
  2. Lab Report / Worksheet
Recognition: No. of University unit(s):  2
* Certificate or letter of completion will be awarded to students who attain at least 75% attendance and pass the assessment (if applicable)
Expected applicants: Students studying S4-S6 or equivalent who must have taken at least one science course which include Biology, Chemistry, Combined Science, Physics, Information and Communication Technology, Design and Applied Technology, Mathematics Extended Module 1 or 2
Organising period: Summer 2021
Application method: SAYT Online application