Data Science from Scratch A Course on First Principles with Python

This course is designed for beginners and aspiring data scientists who want to understand data science from the ground up. Instead of relying on pre-built libraries, you'll learn core data science concepts by implementing them from scratch using Python. This approach helps you build a deep, intuitive understanding of how data science techniques actually work.

What You’ll Learn:

📊 Mathematics for Data Science – Master the basics of linear algebra, probability, and statistics, which form the foundation of data analysis.
🐍 Python for Data Science – Learn how to use Python’s core features to manipulate data, perform computations, and visualize results.
📈 Building Machine Learning Algorithms – Implement essential machine learning models like linear regression, decision trees, and neural networks from scratch, without using libraries like Scikit-learn or TensorFlow.
🛠 Data Cleaning & Processing – Understand how to clean, transform, and handle real-world data to prepare it for analysis.
🚀 Practical Applications – Work on hands-on projects, such as predictive modeling, recommendation systems, and clustering algorithms.

By the end of this course, you will have a solid foundation in data science, enabling you to develop your own algorithms and understand how AI models are built at the core level. Whether you're a beginner or looking to reinforce your knowledge, this course will help you gain a strong conceptual and practical grasp of data science.