Artificial Intelligence and Machine Learning (2023 Spring)

Instructor (Physical): Professor John Sum, Institute of Technology Management
Office/Email: Room 821, CSSM Building / pfsum@nchu.edu.tw (for general enquiries)
Time: Wednesday 14:10-17:00
Course Venue: Room 322, CSSM Building (Physical) / Google Meet (Online)
Course Email: johnsum.nchu@gmail.com (for assignments submission)
Course URL: web.nchu.edu.tw/~pfsum/AIML/AIML2023.html
Consultation: By appointment
*** REMINDER ***

This course is an elective course particularly designed for the ITM NCHU students who have admitted for the MBA program, specialized in Electronic Commerce or Technology Management. Medium of instruction of this course is English, occassionally supplemented with Chinese. The loading of this course is not light. Students are expected to attend all lectures and complete all courseworks. Attendance will not be accounted for a part of the final score. But, absence without proper reason will be.

Professor John Sum is a strict person and sometimes a monster. His expectation on the behavior and the performance of a student is stringent. It is simply because John Sum has been teaching in the area of electronic commerce for more than two decades. Materials in his mind are abundant. Only some of them are extracted and complied as the teaching materials for the course.

*** REMINDER END ***

Prerequisites

Students are expected to have the following skills and knowledge.
  1. Able to read, write, speak and listen in English.
  2. Skillful in the use of word processing software for report writing and presentation.
  3. Skillful in searching information over the Internet.
  4. Knowledge in one of the following subjects: Principles of Computing, Computer Literacy, Introduction to Information Systems, Introduction to Computer Science, Introduction to Information Technologies or other related subjects.
  5. The standard of a coursework report in the doctoral program level as compared with a report in master or undergraduate program level.
Students are expected to have a good health. Then, the students are able to work over serval nights.

Course Outline

Below lists some topics to be covered in this course. Dependent upon the qualification of the students, other topics could be added and some of them could be skipped.
  1. Introduction to AIML/Intelligent Technology. (PDF)
  2. Reading List. (PDF)

Additional Readings

  1. Teammates Instead of Tools: The Impacts of Level of Autonomy on Mission Performance and Human-Agent Teaming Dynamics in Multi-Agent Distributed Teams, (Question sheet).

Assignments

  1. Assignment 1: Questions in the lecture note Introduction to AIML/Intelligent Technology. Deadline: Feburary 21, 2023.

Assessment

Students would need to submit a survey report on any topic of interest. A student could submit a research paper instead. In either cases, students need to give an oral presentation no shorter than 90 mintues in the semester end. It is expected that the report and presentation slides are prepared in English.

Student could opt to present two journal papers. Similarly, the duration of each presentation should be no shorter than 90 mintues and the presentation slides are expected to be prepared in English.