Deep dive into data science concepts, tools, and real-world applications.
Kickstart your data science journey with a friendly, beginner-friendly introduction. Understand what Data Science is, how it works, and where it's used in real life.
Set up your complete Python environment for data science. Install essential libraries, configure Jupyter notebooks, and write your first analysis.
Learn about the core Python libraries used in Data Science, including Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn, and how they fit into a typical workflow.
Learn how we load data from different sources like CSV, Excel, JSON, SQL, and MongoDB into Pandas for analysis.