Regardless of which group of TDs you choose for each of the two courses (Introduction to Machine Learning or Introduction to Deep Learning), a minimal knowledge of Python is required. If you know how to program, learning the basics of Python to easily follow the course is easy. To do so:
If you are a beginner in Python, the following is not for you. You will be in the "Python for Beginners" lab group, which is intended for LIFE, SPECTRUM, or non-computer science students in DS4h. Nevertheless, take the time to review the Python basics presented above.
If you want to be in the "confirmed in Python" lab group, rather intended for computer science students or PhD students regularly programming in Python, try to do the exercises proposed in this notebook.By clicking on "notebook" you download a compressed python jupyter notebook. If this was not done when downloading, you have to unzip the file. To run the notebook, you must have installed "jupyter" and upload the notebook in "jupyter". If this seems very obscure to you... you should not use jupyter notebooks regularly.As an experiment, you can try to open the notebook directly in google colab.
The objective of completing this notebook is to test your skills in installing and using some libraries in Python, with focus on some libraries used in data science projects such as: pandas, seaborn, math and numpy. Since you may not know all commands in details, feel free to look for the corresponding online documentation of these libraries.
If it takes you more than 2 hours to complete the workbook properly, you should take Python classes and opt for the "Beginner's Python" lab group.