Data Science in Chemical Engineering

Overview

This repository contains Python source code and materials for the Data Science course in Chemical Engineering at POLIMI (Politecnico di Milano). The course covers fundamental concepts and practical applications of data science techniques using Python.

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

Technology Stack

• Language: Python (100%)
• Main Libraries: NumPy, Scikit-learn, TensorFlow

Installation and Setup

1. Clone the repository:

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

Other Useful Links

• 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