BIST-master-python-bootcamp

Contents for the scientific python bootcamp of the BIST master of Multidisciplinary Research in Experimental Sciences (2023 course).

The contents of this year's bootcamp are designed based on 2022, 2021, 2020, and 2019 editions.

IMPORTANT: Make sure you have the learning environment ready before coming to the first class on September 14th. Follow the steps below to 1) install python and 2) prepare the MMRES-python-bootcamp2023 repository on your machine.

Suggested python installation

1. Distribution: Anaconda3 with Jupyter or JupyterLab (better JupyterLab). Please, refer to the official Anaconda website and follow downloading and installing instructions.
2. Packages: NumPy, Pandas, SciPy, Matplotlib, Seaborn, Scikit-learn, Statsmodels, bioinfokit*, Pytorch* and Torchvision*. Please note that starred packages are not available after default Anaconda3 setup and thus you should manually install them using Anaconda Prompt. Follow the hyperlinks for further help and be patient, Anaconda might take a considerable amount of time to install certain packages.
3. Git (Optional).

Suggested repository preparation

1. From this same page, use the <> Code green button and then Download ZIP option to store a local copy of this repository (don't forget to unzip it). If you are familiar with Git, you can just clone the repository.
2. Open an Anaconda Prompt and navigate to the folder where the just-downloaded repository is locally stored in your machine (for example, by doing cd C:Users\You\GitHub\MMRES-python-bootcamp2023 or something similar).
3. Type the command jupyter lab (you will see how Jupyter Lab opens a new tab in your default web browser).
4. Check that you can successfully load the first Jupyter Notebook called 01_Intro.ipynb just by double-clicking it (use the "File Browser" pane at the left side of the Jupyter Lab tab).

If you reached this point, you are up and ready to start the bootcamp next September 14th.

Timetable

	Sept. 14th	Sept. 18th	Sept. 21st	Sept. 28th	Oct. 5th	Oct. 9th
10:00-11:00	Set up & Intro (I)	Scipy stats (I)	Pandas (II)	Group Work revision	Numpy	Group Work revision
11:00-12:00	Intro (II)	Pandas (I)	Seaborn	Scipy stats (II)	Intro to ML	Q&A or extra material

	Oct. 16th	Oct. 17th	Oct. 18th	-	-	-
9:00-10:00	Neural Networks	Convolutional Layers	Advanced methods:	-	-	-
10:00-11:00	Backpropagation	Overfitting	NLP	-	-	-
11:00-12:00	Exercise	Regularization	-	-	-	-

Online Resources

• Learn X in Y minutes where X = Python
• The Python Tutorial
• 10 Minutes to Pandas
• SciPy Lecture Notes
• Python Data Science Handbook
• Pythonic Preambulations