Python Programming for Machine Learning (PyML)

Python Programming for Machine Learning (3 ECTS credits) is a course that can be taken as part of the following modules:

In most cases, we do not recommend taking the course as a standalone. That is because the course is not a module (but part of a module), and most examination regulations only approve modules. However, there are exceptions, e.g., for some exchange students. Please carefully check your examination regulations in such a scenario. If we issue a certificate for PyML, you cannot use PyML as part of another module (like CA or ML).

You can contact us at

You can choose between two (almost identical) blocks:


  • Course Period

    April 24th - May 19th 2023 (4 Weeks)

    Weekly Sessions

    Lecture 1

    Thursdays, 16:15 - 17:45 s.t. (online only, recommended)

    Lecture 2

    Friday, 09:00 - 10:30 s.t. (online, TEL106 available for streaming, recommended)

    Q&A / Exercise

    Friday, 10:30 - 12:00 s.t. (TEL 106, optional)


    Christopher Anders

    Panagiotis Tomer Karagiannis

  • Homework deadline: usually Mondays 23:55 (~10 days after the respective second lecture). Late submissions will not be graded!


  • Course Period

    June 5th - June 30th 2023 (4 Weeks)

    Weekly Sessions

    Lecture 1

    Monday, 14:00 - 15:30 (MAR 4033, recommended)

    Lecture 2

    Monday, 15:30 - 17:00 (MAR 4033, recommended)

    Q&A / Exercise

    Thursday, 16:00 - 17:30 (new room: MAR 4057, optional)


    Jannik Wolff

    Panagiotis Tomer Karagiannis

  • Homework deadline: Mondays 23:55 (7 days after the respective lectures). Late submissions will not be graded!

Information valid for PyML A and B

  • Language


    Exams (choose one)

    June 9th, 12:30 - 02:30 p.m. (H 0105 Audimax)

    Jul 12th, 03:00 - 05:00 p.m. (H 0104)

    Jul 25th, 03:00 - 05:00 p.m. (A151)

    Exams reviews (each one valid for any exam)

    June 21st, 04:00 - 05:00 PM (MAR 4057)

    July 20th, 3:30 to 5:00 PM (MAR 4.057)

    July 28th, 02:00 - 04:00 p.m. (MAR 4057)





  • You must be enrolled on ISIS to submit homework. If you do not register on time, you cannot pass the course.

  • Homework assignments must be submitted every week.
  • Homework assignments must be completed by yourself . Group work is not allowed and will receive 0 points.

  • Homework is passed with 50/100 points or more.


  • Participation in the exam requires successful completion of all homework.

  • The exam requires registration on ISIS. Registration via QISPOS is not necessary.
  • For the PyML exams, you are allowed to take one A4 sheet of paper with handwritten text on both sides into the exam. Printed text is not allowed.

  • You need to pass the PyML exam BEFORE taking the Cognitive Algorithms/ Machine Learning 2 exam to obtain the credits for this course. The PyML exams are usually well before the registration deadlines of the respective courses. Exception: if you choose the last exam on the 25th of July and plan to take the first Cognitive Algorithms exam on the 2nd of August, which has its registration deadline on the 26th of July, and its withdrawal deadline on the 31th of July, we recommend to register for the CA exam as soon as possible, and then withdraw from the registration in case you failed the PyML exam.

  • In case you fail the PyML exam, you can retry as many times as you like, however, you still need to pass the exam before taking the CA/ML-2 exam. Therefore, we recommend that you take the earliest PyML exam possible in order to prevent the completion of your module to be delayed until next semester/year.

Passing the course

  • The course is passed if the exam is passed (grade 4.0 or better) and all homeworks are completed successfully.

  • The final course grade is determined by the exam only. The course grade is irrelevant for most students because it does not count for CA/ML.

Frequently Asked Questions (FAQ)

  • Where is the link for the class?

    • Links for the online lectures and exercises will be announced on ISIS just before they start.
  • Is prior programming/Python knowledge necessary?

    • Knowledge of elementary programming concepts (in Python or another language) will be helpful. Lack of such knowledge will significantly increase the time demand of the class.
  • Which exam is compatible with PyML A/B?

    • All exams are compatible with PyML A or B. You can choose the exam that fits your time schedule best.
  • May I participate in the class during this semester and take part in the corresponding module in one of the following semesters ?

    • Yes, just after you've passed the class, your results are also valid for the next semesters.
  • I've already successfully passed all of the homework in the previous semester but failed/missed the exam. Should I resubmit them again?

    • No, you do not need to resubmit the homework. Please enroll in the ISIS course for the new semester and register for the exam on ISIS once possible (registration via the examination office is not possible/necessary).
  • Until when do I have to register at QISPOS? I do not have an ISIS account yet.

    • You have to register for a corresponding module, either ML or CA, until the deadline. Usually it is six weeks before the first exam.
  • What are the Q&A/exercise sessions?

    • You can ask questions regarding the lectures or the homework in these sessions.
  • I will not be able to attend a lecture. Is this a problem?

    • All learning materials will be made accessible online. You only need to submit your homework before the deadline. Ask in the ISIS forum if you have questions regarding lecture content.

Students from other universities

If you are not a student at TU and want to earn credit, you have to solicit ''Nebenhörerschaft'':

Please make sure to trigger the above process on time. You may need to go through some bureaucracy to attain ISIS (the university's web portal) access, which is necessary to submit the mandatory homework.

IDA Wiki: Main/SS23_PyML (last edited 2023-08-08 09:33:55 by JannikWolff)