Guided path
Data Science Roadmap
Five hands-on Python modules covering arrays, data frames, visualisation, and machine learning — then the maths that ties it all together.
NumPy
Create, index, filter, reshape, and analyze numeric arrays with NumPy, the base library for data science and machine learning.
pandas
Load, clean, filter, group, and combine table-shaped data with pandas Series and DataFrames.
Matplotlib
Draw clear line, bar, scatter, histogram, and pie charts with Matplotlib, arrange them in subplots, and save them as files.
Seaborn
Explore tidy data with Seaborn's relational, distribution, categorical, matrix, and regression charts, then theme and finish them.
Scikit-learn
Train, evaluate, and tune regression, classification, and clustering models with scikit-learn, from train and test splits to pipelines and saved models.