Data Science in Chemical Engineering

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This repository contains the materials shown during the practical sessions of the course Data Science in Chemical Engineering taught at Politecnico di Milano by Professor Alessandro Stagni.

Course Structure

The repository is organized into 12 main modules:

1. Hands On Python - Introduction to Python programming
2. SVD - Singular Value Decomposition
3. PCA - Principal Component Analysis
4. Unsupervised Machine Learning - Clustering and dimensionality reduction
5. Supervised Machine Learning - Classification and prediction
6. Regression - Linear and non-linear regression techniques
7. Model Selection - Methods for choosing and validating models
8. Neural Networks - Fundamentals of neural networks
9. Deep Learning - Advanced neural network architectures
10. Reduced Order Models - Model order reduction techniques
11. Physics Informed Models - Integration of physical principles with data science
12. Pandas and Imbalanced Datasets - Data manipulation and handling imbalanced data

Installation and Setup

Consult also the detaield Installation guide

Prerequisites

• Python 3.10 or higher (recommended: Python 3.12)
• conda (Anaconda or Miniconda)

Quick Start

Clone the repository:

git clone https://github.com/Riccaraccio/Data-Science.git
cd Data-Science

Create and activate the conda environment:

conda create -n data-science python=3.12
conda activate data-science

Installation Options

Installs all required packages including PyTorch, scikit-learn, Jupyter, and visualization tools:

pip install -e .

Launching Jupyter

After installation, you can start JupyterNotebook for interactive work:

jupyter notebook

Some useful material

• This page offers a concise Python programming tutorial that teaches the language basics through practical examples: https://learnxinyminutes.com/python/
• W3Schools is a popular educational website that provides free tutorials, references, and examples: https://www.w3schools.com/python/
• Github repository containing free programming books: https://github.com/EbookFoundation/free-programming-books/tree/main
• Github repository containing ideas for programming exercises: https://github.com/practical-tutorials/project-based-learning