Data Science and Machine Learning with Python

Modern data science combines programming, statistical thinking, and machine learning to turn raw information into actionable insights. This text-based course guides you step by step through foundational concepts to practical data workflows. You will start with core terminology and essential data analysis principles before advancing to predictive models and artificial intelligence fundamentals. What you'll learn: Learn Python fundamentals and modern data manipulation libraries for structured analysis. Understand exploratory data analysis and statistical evaluation techniques. Apply supervised and unsupervised machine learning algorithms to real-world datasets. Practice building end-to-end data pipelines and evaluating model performance. Explore modern AI concepts including prompt engineering basics and foundational MLOps workflows. The material starts with foundational data principles and progressive Python exercises, gradually moving into model training and deployment concepts. This course is designed for beginners and aspiring data practitioners with no prior programming or data science background. Start reading today to build practical, in-demand data science skills.