COMP7404A - Computational intelligence and machine learning

Semester 2, 2017-18

Dr. Dirk Schnieders
Teaching assistant
Mr. Zhenfang Chen
Syllabus This course will teach a broad set of principles and tools that will provide the mathematical and algorithmic framework for tackling problems using Artificial Intelligence (AI) and Machine Learning (ML). AI and ML are highly interdisciplinary fields with impact in different applications, such as, biology, robotics, language, economics, and computer science. AI is the science and engineering of making intelligent machines, especially intelligent computer programs, while ML refers to the changes in systems that perform tasks associated with AI.

Topics may include a subset of the following: problem solving by search, heuristic (informed) search, constraint satisfaction, games, knowledge-based agents, supervised learning, unsupervised learning; learning theory, reinforcement learning and adaptive control.
Introduction by Instructor This course will cover several topics in AI and ML. We will start with traditional AI techniques including search (with and without adversary), constraint satisfaction problems and markov decision processes. We will cover machine learning including (deep) reinforcement learning, linear regression, support vector machines and neural networks.
Learning Outcomes
Course Learning Outcomes Relevant Programme Learning Outcomes
CLO1. Understand the fundamental concepts of computational intelligence and machine learning PLO.5, 6, 7, 8, 9, 16
CLO2. Demonstrate awareness of the major challenges and risks facing computational intelligence and the complexity of typical problems within the field PLO.4, 6, 7, 8, 13, 14, 15
CLO3. Able to implement solutions to various problems in computational intelligence PLO.6, 7, 8, 9, 10, 11, 12
View Programme Learning Outcomes
Pre-requisites Good programming, knowledge of data structures, algorithms, probability and linear algebra.
Compatibility Nil
Topics covered
Course Content No. of Hours Course Learning Outcomes
1. Introduction 2 CLO1, CLO2
2. Search to Solve Problems 6 CLO1, CLO2, CLO3
3. Constraint Satisfaction Problems 3 CLO1, CLO2, CLO3
4. Adversarial Search 3 CLO1, CLO2, CLO3
5. Markov Decision Processes 3 CLO1, CLO2, CLO3
6. Reinforcement Learning 3 CLO1, CLO2, CLO3
7. Linear Regression / Support Vector Machines 3 CLO1, CLO2, CLO3
8. Deep Neural Networks 3 CLO1, CLO2, CLO3
9. Group Presentations 6 CLO3
Description Type Weighting * Examination Period ^ Course Learning Outcomes
Group Project Continuous Assessment 30% - CLO3
Written Midterm Examination Continuous Assessment 20% - CLO1, CLO2
Written exam covering all taught content of the course Written Examination 50% May 7 to 26, 2018 CLO1, CLO2
* The weighting of coursework and examination marks is subject to approval
^ The exact examination date uses to be released when all enrolments are confirmed after add/drop period by the Examinations Office.  Students must oblige to the examination schedule. Students should NOT enrol in the course if they are not certain that they will be in Hong Kong during the examination period.  Absent from examination may result in failure in the course. There is no supplementary examination for all MSc curriculums in the Faculty of Engineering.

For reference:
Course materials Recommended readings:
  • Artificial Intelligence: A Modern Approach (3rd Edition), Stuart Russell and Peter Norvig
  • Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto
Session dates
Date Time Venue Remark
Session 1 20 Jan 2018 (Sat) 9:30am - 12:30pm CB-A  
Session 2 27 Jan 2018 (Sat) 9:30am - 12:30pm CB-A  
Session 3 3 Feb 2018 (Sat) 9:30am - 12:30pm CB-A  
Session 4 10 Feb 2018 (Sat) 9:30am - 12:30pm CB-A  
Session 5 24 Feb 2018 (Sat) 9:30am - 12:30pm CB-A  
Session 6 3 Mar 2018 (Sat) 9:30am - 12:30pm CB-A  
Session 7 17 Mar 2018 (Sat) 9:30am - 12:30pm CB-A  
Session 8 24 Mar 2018 (Sat) 9:30am - 12:30pm CB-A  
Session 9 7 Apr 2018 (Sat) 9:30am - 12:30pm CB-A  
Session 10 21 Apr 2018 (Sat) 9:30am - 12:30pm CB-A  
Session 11 21 Apr 2018 (Sat) 1:30pm - 4:30pm CPD-LG.18  
Session 12 28 Apr 2018 (Sat) 9:30am - 12:30pm CB-A  
CB - Chow Yei Ching Building CPD - Central Podium Levels (Centennial Campus)
Add/drop 15 January, 2018 - 28 January, 2018
Quota 100