Course syllabus

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TME286, SP3, 2023. Course memo:

The course is offered by the department of Mechanics and Maritime Sciences

General information

The course will be given only on-site at Chalmers. There will be no remote (Zoom) lectures. More information will follow in the first lecture.

Contact details

During the course, we strive to be available as much as possible. You are welcome to ask questions at any time, e.g. in the lectures (and you may also ask questions via e-mail or telephone). You are always welcome at our offices. You do not need to make an appointment, but since we are not always in our offices it's a good idea to first check that we are there (e.g. via e-mail or telephone).

Lecturer and examiner:

Professor Mattias Wahde, tel.: 031 772 3727, e-mail: mattias.wahde@chalmers.se

Course assistant:

Tianyou Li, tianyou.li@chalmers.se

Finding our offices: Go to Hörsalsvägen 7, enter the building (nya M-huset), so that you have Café Bulten on your right as you enter. Then go up one flight of stairs, and enter the corridor (Vehicle Engineering and Autonomous Systems). If the door is locked, please dial the appropriate number, as shown in the list beside the door (e.g. 031 772 3727 for Mattias).

Course purpose

The aim of the course is for the students to gain knowledge regarding conversational AI in general and intelligent conversational agents, in particular. Students will learn about text preprocessing, statistical language models, text classification, and conversational agents, both chatbots and (most importantly) task-oriented agents. Emphasizing interpretable systems (rather than black box models), the course covers both theoretical aspects and the practical aspects related to actual implementation of conversational agents. Applications and ethical aspects are considered as well.

Schedule

The course schedule is given below. The lectures can also be found in TimeEdit

Date Room Time  Content
20230117 HC3 08.00-09.45 Course introduction and motivation; Brief description of the topics covered in the course; Introduction to conversational AI.
20230118 HA3 13.15-17.00

Text preprocessing (tokenization, normalization, vectorization etc.), introduction to C# programming 
20230124 HC3 08.00-09.45 Statistical language models (I), 
20230125 HA3 13.15-17.00 Statistical language models (II), Handout of Assignment 1
20230131 HC3 08.00-09.45 Text classification with classical methods.
20230201 HA3 13.15-15.00

Text classification with (DNNs), performance evaluation.
Interpretable AI, ethical aspects of conversational AI, Handout of Assignment 2
Note: We have 4 hours in TimeEdit (just in case), but we probably only need 2 hours this time.
20230207 HC3 08.00-09.45 Chatbots
20230208 --- --- No lecture
20230214 HC3 08.00-09.45 Task-oriented agents. DAISY, Part 1 Handout of Assignment 3
20230215 HA3 13.15-17.00 DAISY, Part II, Advanced C# programming, Assignment work session (~2 hours)
20230221 HC3 08.00-09.45 Input and output modalities. Applications and historical overview
20230222 HA3 13.15-17.00 Assignment work session (lecturer and assistant as tutors), Handin of Assignment 1
20230228 --- --- No lecture (Note!)
20230301 HA3 13.15-17.00

Assignment work session (lecturer and assistant as tutors), Handin of Assignment 2
20230307 HC3 08.00-09.45

Assignment work session (lecturer and assistant as tutors).
20230308 HA3 13.15-17.00

Course summary; chatbot demonstration (students demonstrating their chatbots from Assignment 3), Handin of Assignment 3

Course literature

The course literature will consist of lecture notes (also with some links to various scientific papers and web resources), which will be provided gradually during the course.
Note that, due to the large changes in the course, the compendium from previous years is now outdated. All lecture notes will be provided on the Modules page.

Course design

The course consists of a sequence of lectures, usually two per week (but note that there are some exceptions; see above). Several sessions, especially towards the end of the course, are work sessions, during which the students will work with their assignments. 

Changes made since the last occasion (2022)

The course has been modified a bit, mainly regarding statistical language model. The topic of linear regression (in text classification) has been added. Moreover, the topic of interpretability is now emphasized even more strongly.

Learning outcomes

After completion of the course the student should be able to...

  • Understand and implement basic text preprocessing
  • Understand and use statistical language models.
  • Carry out text classification with several different methods
  • Implement chatbots (in C# .NET)
  • Implement (aspects of) task-oriented agents in (in C#. NET) 
  • Describe and discuss various input and output modalities (e.g. speech) in conversational agents
  • Describe and compare various different (applications of) intelligent agents.
  • Describe and discuss interpretable AI, and be able to contrast interpretable models with black box models
  • Describe and discuss the ethical implications of conversational agents.

Examination 

Examination: There will be three assignments, worth a total of 100 p. More details will follow when the course starts.

The dates for handing in the assignments can be found in the schedule above. The detailed requirements will be given in connection with each assignment. In order to pass the course, students must hand in satisfactory solutions to all four assignments. Grades will then be set as follows:

Grade 3: Up to 60p

Grade 4: [61, 80] p

Grade 5: [81-100] p

Note: All deadlines are at 23.59.59 on the specified dates, and it is the time when the submission is received that counts. Submissions that are handed in late will receive a lower score, as described in each assignment document. The possibility of submitting assignments will be closed at midnight on 20220318.

Re-examination, grade improvement etc.: It is possible for students to improve their grade by resubmitting assignments. However, after the final submission deadline during the course (20230317) resubmission is only allowed in connection with the re-exam periods in August (2022) and January (2023). 

Note: All submissions must be handed in via the Canvas page. E-mailed submissions will not be considered.

 

 

Course summary:

Date Details Due