Tutorial Series // Data Science
The Complete Data Science Tutorial
NumPy, pandas, statistics, visualisation, and machine learning — from raw data to decisions. Every topic ships working code.
- 01 Introduction to Data Science & Pandas Start your data science journey with Pandas, the powerhouse library for data manipulation and analysis in Python. 15 min →
- 02 Data Aggregation & Grouping Master the split-apply-combine pattern to analyze data across different categories and dimensions. 12 min →
- 03 Data Visualization with Matplotlib & Seaborn Turn numbers into insights by creating compelling charts and graphs using Python visualization libraries. 15 min →
- 04 Feature Engineering and Data Preprocessing Learn how to transform raw data into a format that machine learning models can understand and learn from. 14 min →
- 05 Machine Learning with scikit-learn Train your first machine learning models using the industry-standard scikit-learn library. 18 min →
- 06 Model Evaluation and Cross-Validation Learn how to properly test your models to ensure they generalize to unseen data, avoiding the trap of overfitting. 15 min →
- 07 Deep Learning Fundamentals with PyTorch Step into the world of neural networks and deep learning using PyTorch, the framework favored by researchers and industry. 20 min →
- 08 End-to-End Data Science Project Tie everything together by building and deploying a complete data science pipeline from raw data to a working API. 25 min →