Introduction to Data Science

Discover what data science is, the essential tools you'll use, and the workflow for transforming raw data into insights.

Master the foundation of scientific computing in Python by learning to create and manipulate NumPy arrays efficiently.

Unlock NumPy's true power with broadcasting, vectorized operations, and mathematical aggregations for lightning-fast data processing.

Master the fundamentals of Pandas, Python's premier data manipulation library, and learn to work with Series, DataFrames, and real-world datasets.

Master essential data manipulation techniques including selecting rows and columns, filtering with conditions, and modifying DataFrame structure.

Learn essential data cleaning techniques including handling missing values, removing duplicates, and converting data types for analysis-ready datasets.

Master advanced data analysis techniques with grouping, aggregation, and sorting to extract powerful insights from your data.

Create professional, publication-quality visualizations to communicate data insights effectively using Matplotlib.

Create beautiful statistical visualizations with minimal code using Seaborn, the high-level visualization library built on Matplotlib.

Apply everything you've learned to perform a complete exploratory data analysis on a real-world dataset, from initial inspection to final insights.