← All Tutorials
ThePythonBook

Data Science & Machine Learning

NumPy, Pandas, Matplotlib, SciPy, and scikit-learn

20tutorials
117exercises
535minutes
1995XP
1

NumPy Arrays: Create, Index, Slice, and Reshape

30m
2

NumPy Operations: Element-wise Math, Aggregations, and ufuncs

25m
3

NumPy Broadcasting: Operate on Arrays of Different Shapes

25m
4

NumPy Linear Algebra: Dot Products, Inverses, and Eigenvalues

25m
5

Pandas: Create, Load, and Explore DataFrames

30m
6

Pandas Indexing: loc, iloc, Boolean Indexing, and Selection

25m
7

Pandas Data Cleaning: Missing Values, Duplicates, and Outliers

30m
8

Pandas merge(), join(), concat(): Combine DataFrames Like SQL

25m
9

Pandas GroupBy: Split-Apply-Combine for Powerful Aggregations

30m
10

Pandas apply(), map(), transform(): Custom Data Transformations

25m
11

Pandas String and DateTime Operations for Real-World Data

25m
12

Pandas Pivot Tables and Cross-Tabulation for Business Analysis

25m
13

Matplotlib: Create Line, Bar, Scatter, and Pie Charts

25m
14

Advanced Matplotlib: Subplots, Dual Axes, Styles, Annotations

25m
15

Data Visualization: Choose the Right Chart and Tell a Story

25m
16

SciPy Statistics: Distributions, Hypothesis Tests, and Correlations

30m
17

Build Your First ML Model: Linear Regression with scikit-learn

30m
18

Python Classification: Build a Classifier with scikit-learn

30m
19

Evaluating ML Models: Cross-Validation, Metrics, and Overfitting

25m
20

K-Means Clustering: Find Patterns in Data Without Labels

25m
MetaprogrammingGenerative AI & LLMs

Save your progress across devices

Never lose your code, challenges, or XP. Sign up free — no password needed.

Already have an account?