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Frequently asked questions

For further questions, please contact Nicki.

Is it possible to attend the course fully online ❔

Mostly yes. All exercises are provided online and lectures will be recorded and streamed. However, do note that

  • For project days (see which days in the time plan) you will need to agree with your project group that you are working from home.
  • The oral part of the exam takes place on campus. EuroTEQ students are exempt from this rule. If you have an extremely good reason for not being able to come to campus on the exam date, please contact us within the first week of the course.
  • We have limited TA resources and will be prioritizing students coming to campus for help. If you are attending online, feel free to ask questions on our Slack channel and we will help to the best of our ability.

Overall we try to support flexible learning as much as possible with some limitations.

What are the prerequisites for taking this course ❔

We recommend that you have a basic understanding of machine learning concepts such as what a dataset is, what probabilities are, what a classifier is, what overfitting means etc. This corresponds to the curriculum covered in course 02450. The actual focus of the course is not on machine learning models, but we will be using these basic concepts throughout the exercises.

Additionally, we recommend basic knowledge about deep learning and how to code in Pytorch, corresponding to the curriculum covered in 02456. From prior experience, we know that not all students have gained knowledge about deep learning models before this course, and we will be covering the basics of how to code in PyTorch in one of the first modules of the course to get everyone up to speed.

I will be missing X days of the course, will that be a problem ❔

Depends. The course is fairly intensive, with most students working from 9-17 every day. If you already know that you will be missing X days of the course, then I highly recommend that you go through some of the first sessions before the course starts to give yourself a bit of breathing room. If you are not able to do so, please be aware that an additional effort may be needed from you to keep up with your fellow students.

How many should we be in a group for the projects ❔

Between 3 and 5. The projects are designed to be done in groups meaning that we intentionally make them too big for one person to do alone. Luckily, a lot of the work that you need to do can be done in parallel, so it is not as bad as it sounds.

When will the exam take place ❔

The oral part of the exam, which is a small project demo, always falls on the last day of the course. For January 2024, this means the 19th. The written part which is a small project report, should be handed in at midnight on the final course day.

Where can I find information regarding the exam ❔

Look at the bottom of this page. Details will be updated as we get closer to the exam date.

Can I use ChatGPT or similar tools for the exercises, project, exam report (coding + writing) ❔

Yes, yes, and yes, but remember that its a tool and you need to validate the output before using it. We would prefer for the exam report that you formulate the answers in your own words because it is intended for you do describe what you have been doing in your project. The I in LLM stands for intelligence.

I am a foreign student and my home university doesn't accept pass/not pass, what can I do ❔

We can give a grade on the Danish 7-point grading scale for foreign students who need it, where their home university does not accept pass/no-pass. You need to contact the course responsible Nicki within the first week of the course to request this. Secondly, make sure to also inform us about it during the oral part of the exam because we need to ask you additional questions to be able to give an exact grade.

I am a EuroTEQ student, any special rules for me ❔

You will be allowed to attend the oral part of the exam online and we will provide a special Slack channel for you, trying to make sure that you get the same help as students from DTU who can attend the course on campus.