Data Science curriculum

Learn Data Science

Five Python modules that take you from raw arrays to trained models — NumPy, pandas, Matplotlib, Seaborn, and Scikit-learn.

5 modules · View Data Science roadmap

Module 01Intermediate

NumPy

Create, index, filter, reshape, and analyze numeric arrays with NumPy, the base library for data science and machine learning.

7 hours 55 min19 lessons

Module 02Intermediate

pandas

Load, clean, filter, group, and combine table-shaped data with pandas Series and DataFrames.

9 hours 10 min22 lessons

Module 03Intermediate

Matplotlib

Draw clear line, bar, scatter, histogram, and pie charts with Matplotlib, arrange them in subplots, and save them as files.

8 hours 45 min21 lessons

Module 04Intermediate

Seaborn

Explore tidy data with Seaborn's relational, distribution, categorical, matrix, and regression charts, then theme and finish them.

6 hours 40 min16 lessons

Module 05Intermediate

Scikit-learn

Train, evaluate, and tune regression, classification, and clustering models with scikit-learn, from train and test splits to pipelines and saved models.

7 hours 30 min18 lessons