Learn how to write clean Python code and apply it to data manipulation, statistical analysis, and visualization. Through practical examples, you’ll learn to load, clean, transform, and visualize data while practicing best coding practices like modular design and error handling.

This comprehensive master course covers the full data science lifecycle — from data collection through modeling and deployment. Designed for aspiring data scientists, it blends theory, statistics, machine learning, data visualization, and real-world projects. You'll learn Python-based tools like pandas, scikit-learn, and TensorFlow to develop end-to-end
pipelines.
This course advances your Python-based analytics skills with automation, web scraping, API consumption, NLP, and dashboarding. It focuses on end-to-end automated analytics workflows.