Course syllabus

Course memo

TME286  lp3 VT22 (7.5 hp)

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

General information

The course will be given on-site at Chalmers. More information will follow before 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. However, due to the pandemic, we can only receive one (1) student at a time, and (of course) only if you are symptom free. You do not need to make an appointment, but since we are not always in our offices (in the current situation, we mostly work from home) 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: 772 3727, e-mail: mattias.wahde@chalmers.se
Course assistant: 
Björnborg Nguyen, e-mail: bjornborg.nguyen@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 extension, as shown in the list beside the door (e.g. 3727 for Mattias).

Course purpose

The aim of the course is for the students to gain knowledge regarding natural language processing (NLP) in general and intelligent conversational agents, in particular. Students will learn about 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

The Zoom link for the lectures is:

https://chalmers.zoom.us/j/2039626788 (Links to an external site.)

Passcode: 2020FFR105

Notes
(1) Please strive to attend the lecture in the lecture room (rather than on Zoom) provided that you are well, of course. The equipment for broadcasting the meeting via Zoom may or may not work (it varies between lecture rooms), and I will prioritize giving the lecture rather than trying to fix technical glitches. In case the Zoom connection fails, note that the slides from each lecture will be uploaded just before the lecture, though (see the Modules page)

(2) The passcode is used to prevent abuse. Please do not share with anyone not taking the course.

Course literature

The course literature will consist of lecture notes (also with some links to various scientific papers), 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 (2021)

The course has been modified significantly, now emphasizing natural language processing in general (not only conversational agents).

Learning outcomes

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

• Understand and implement basic text processing
• Understand statistical language models.
• Implement chatbots (in C# .NET)
• Implement a task-oriented agent in (in C#. NET) 
• Implement 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 four 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 (20220318) 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.