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STEM1040 A Trilogy of Hands-on Machine Learning 親身體驗機器學習三部曲
From Monday, July 26, 2021
To Thursday, August 05, 2021
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Course Outline:
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(Last update on: 11 March 2021)

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Key facts for Summer 2021:
Date: 26 - 30 July, 2, 3, 4*, 5* August 2021 (42 Hours)
Time: 9:30 am – 4:30 pm
Teaching Platform:   Face to Face  (The Chinese University of Hong Kong) #
Enrollment:   40
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
Tuition Fee: HKD 3500.00
(Students who have attended all sessions will be granted a HKD 500 scholarship)
Lecturer:

Dr. LAM King Tin (Department of Computer Science and Engineering, Faculty of Engineering, CUHK)
Dr. PAN Li Lily (Department of Mathematics, Faculty of Science)

* This date is reserved for make-up classes in case there is any cancellation of classes due to unexpected circumstances.
# This course is offered face-to-face lessons at CUHK campus. It may switch to online teaching in accordance with the pandemic development and the policy of the university.

 

Introduction:

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.

近年來,人工智能(AI)浪潮席捲全球。未來,智能聊天機器人,虛擬助手和自動駕駛汽車等人工智能設備和服務將逐步融入我們的生活。「機器學習」領域中的突破是目前AI迅速發展的主要驅動力。機器學習利用樣本數據來訓練計算機自主完成任務,而非依賴人工編程。作為機器學習的一個重要分支,「深度學習」在解決如圖像分類,人臉識別和自然語言處理等智能認知問題上取得了豐碩的成果。

本課程透過「三部曲」(數學概念,算法和編程)訓練讓同學親自動手探索機器學習。首先,我們會介紹什麼是機器學習、它如何運作及其應用層面。之後,我們會講解機器學習背後的數學和理論基礎,並分析「人工神經網絡」的代碼,以展示如何將理論轉化為實踐。最後,我們會教導學員使用Python編程語言,TensorFlow和Keras等機器學習框架來實現一些有趣的AI應用(例如:遊戲)。

 


Programme sponsored by: Shanghai Fraternity Association
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. Appreciate the basic principles and applications of artificial intelligence
  2. Explain the basic mathematical and theoretical concepts behind machine learning
  3. Understand how artificial neural networks and deep learning work
  4. Gain hands-on experience in Python programming for machine learning applications
Learning Activities:
  1. Lectures
  2. Exercise and Assignment
  3. LabDemos/Guest Talk
Medium of Instruction: Cantonese supplemented with English
Assessment:
  1. Short answer test or exam
  2. Lab Report
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