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STEM1040 A Trilogy of Hands-on Machine Learning 亲身体验机器学习三部曲
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.

近年来,人工智能(AI)浪潮席卷全球。未来,智能聊天机器人,虚拟助手和自动驾驶汽车等人工智能设备和服务将逐步融入我们的生活。「机器学习」领域中的突破是目前AI迅速发展的主要驱动力。机器学习利用样本数据来训练计算机自主完成任务,而非依赖人工编程。作为机器学习的一个重要分支,「深度学习」在解决如图像分类,人脸识别和自然语言处理等智能认知问题上取得了丰硕的成果。

本课程透过「三部曲」(数学概念,算法和编程)训练让同学亲自动手探索机器学习。首先,我们会介绍什么是机器学习、它如何运作及其应用层面。之后,我们会讲解机器学习背后的数学和理论基础,并分析「人工神经网络」的代码,以展示如何将理论转化为实践。最后,我们会教导学员使用Python编程语言,TensorFlow和Keras等机器学习框架来实现一些有趣的AI应用(例如:游戏)。

 


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