Python Refresher Labs – MSc Data Science, Centrale Lille

This repository contains lab assignments for Python Refresher course taken during the MSc in Data Science program at Centrale Lille (2025-2026).

The labs focus on applying various Python libraries to practical tasks.

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Covered topics and libraries

• Managing Python environments
• Project structure
• Unit testing
• Numpy and linear algebra
• Pandas and data processing
• Matplotlib and Seaborn for visuslization
• Scikit-learn for training ML models
• Image processing
• Code acceleration with Cython
• Code acceleration with Numba
• Parallel computing with Dask

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Repository structure

python-labs/
│
├── lab1_python_environment_basics/
├── lab2_numpy_pandas_matplotlib/
├── lab3_titanic_dataset_fourier_transform/
├── lab4_cython_numba/
├── lab5_seaborn_dask_multiprocessing/
│
├── README.md
└── requirements.txt

Each lab folder contains:

• Jupyter notebook
• datasets (if applicable)
• additional files (if applicable)

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Skills

These labs demonstrate practical experience with:

• Python software development and project structuring
• Virtual environments and dependency management
• Writing and running unit tests
• Numerical computing with NumPy
• Data manipulation and analysis with Pandas
• Data visualization with Matplotlib and Seaborn
• Training machine learning models with Scikit-learn
• Image processing workflows in Python
• Code optimization using Cython and Numba
• Parallel and distributed computing with Dask
• Performance profiling and optimization of Python code

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Author

Danila Pechenev

MSc Data Science – Centrale Lille