Deep Learning” 2021 Course rules

24.02.2021

Instructor: Jan Chorowski
Office hours: pick a slot using the appointment page.

Teaching Assistants:

Marek Adamczyk

Mikołaj Słupiński

Michał Stypułkowski

Course language:

The course is in English. The lectures will be in English, task lists and class discussion will be in English, and the exam will be in English.

Honesty and cheating:

Cheating is not accepted! All transgressions will be penalized (up to failing the course), and all cases will be reported.

Course web page and online presence:

Static course information, and quizzes will be posted in SKOS. Course announcements, communications and lectures will be on MS Teams. Points and grades will appear in USOSweb (starting as soon as the groups are imported there from the Enrolment System).

Task lists and lecture notes will be posted to Github: https://github.com/janchorowski/dl_uwr.

You can send us anonymous feedback through the semester using the anonymous form.

Important: Please contact us in course matters through MS Teams only, preferring global channels unless your matter is very personal. We reserve the right to not respond to emails, especially to ones sent to our personal addresses! We will try to answer on Teams within a business day.

Attendance:

Lectures: will be on-line on MS-Teams. Recordings will be available in Teams.

Labs: you have to hand in your solutions over a MS-Teams video call.

Projects: we will have a final presentations session, which will be mandatory for everyone.

Grading:

Lectures:

There will be a final exam (quiz and oral) at the end of the term. Outstanding lab grades may warrant an exemption form part of the exam.

Labs:

We will have task lists worth about 60 points and a larger assignment (the project) worth about 40 (and so the grand total will be about 100 points). To pass the lab+class you must earn at least half of the points for the lists and half of the points for the project.
The task lists will have several bonus points, and you can get extra points for submitting improvements to course materials.

Task lists:

We will have 5 lab assignments, each for about 2 weeks (you will have to submit some problems in the first week, though).

You can submit lab assignments late, with a 20% points penalty for each full late day.

Heads Up: the late submissions are graded lazily. To stop the clock you must prove that you did the assignment on time (mark a revision in Colab, as shown below). Please ask the instructor to grade your solution during the next lab session, we may refuse to grade them if you want to show them with a larger delay. Whenever you hand in lab solutions, you must know the questions. We will not grade late submissions remotely or over email, you still need to present them in class.

Projects:

Class projects are large! You will work in groups of 2-4 students and will have to make several progress reports. Tentative timeline:

by beginning of May - propose project topic, make a short presentation for your
May and June (6 weeks) - prepare 2 shorter progress presentations for your lab group
End of semester - prepare:

a final presentations, for the whole class
a report.

I will give you templates for the presentations.