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Machine Learning for Everyone

Learn machine learning even if you have no coding experience with this collection of tutorials covering supervised learning, unsupervised learning, and deep learning.

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Loved by learners at thousands of companies

1
Theory
Understanding Machine Learning

An introduction to machine learning with no coding involved.

2 hours

Hadrien Lacroix Headshot

Hadrien Lacroix

Curriculum Manager at DataCamp

2
Python
Introduction to Python

Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.

4 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist

3
Python
Intermediate Python

Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

4 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist

4
Python
Introduction to Functions in Python

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

3 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist

5
Python
Python Toolbox

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

4 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist

6
Python
Statistical Thinking in Python (Part 1)

Build the foundation you need to think statistically and to speak the language of your data.

3 hours

Justin Bois Headshot

Justin Bois

Lecturer at the California Institute of Technology

7
8
Python
Unsupervised Learning in Python

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

4 hours

Benjamin Wilson Headshot

Benjamin Wilson

Director of Research at lateral.io

9
Python
Linear Classifiers in Python

In this course you will learn the details of linear classifiers like logistic regression and SVM.

4 hours

Mike Gelbart Headshot

Mike Gelbart

Instructor, the University of British Columbia

10
Python
Machine Learning with Tree-Based Models in Python

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

5 hours

Elie Kawerk Headshot

Elie Kawerk

Senior Data Scientist

11
Python
Extreme Gradient Boosting with XGBoost

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

4 hours

Sergey Fogelson Headshot

Sergey Fogelson

Head of Data Science, TelevisaUnivision

12
Python
Cluster Analysis in Python

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

4 hours

Shaumik Daityari Headshot

Shaumik Daityari

Business Analyst at American Express

13
Python
Dimensionality Reduction in Python

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

4 hours

Jeroen Boeye Headshot

Jeroen Boeye

Machine Learning Engineer @ Faktion

14
Python
Preprocessing for Machine Learning in Python

Learn how to clean and prepare your data for machine learning!

4 hours

James Chapman Headshot

James Chapman

Curriculum Manager, DataCamp

15
Python
Machine Learning for Time Series Data in Python

This course focuses on feature engineering and machine learning for time series data.

4 hours

Chris Holdgraf Headshot

Chris Holdgraf

Fellow at the Berkeley Institute for Data Science

16
Python
Feature Engineering for Machine Learning in Python

Create new features to improve the performance of your Machine Learning models.

4 hours

Robert O'Callaghan Headshot

Robert O'Callaghan

Director of Data Science, Ordergroove

17
Python
Model Validation in Python

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

4 hours

Kasey Jones Headshot

Kasey Jones

Research Data Scientist

18
Python
Introduction to Natural Language Processing in Python

Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.

4 hours

Katharine Jarmul Headshot

Katharine Jarmul

Founder, kjamistan

19
Python
Feature Engineering for NLP in Python

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

4 hours

Rounak Banik Headshot

Rounak Banik

Data Scientist at Fractal Analytics

20
Python
Introduction to TensorFlow in Python

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

4 hours

Isaiah Hull Headshot

Isaiah Hull

Economist

21
Python
Introduction to Deep Learning in Python

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.

4 hours

Dan Becker Headshot

Dan Becker

Data Scientist and contributor to Keras and TensorFlow libraries

22
Python
Introduction to Deep Learning with Keras

Learn to start developing deep learning models with Keras.

4 hours

Miguel Esteban Headshot

Miguel Esteban

Data Scientist & Founder

23
Python
Advanced Deep Learning with Keras

Learn how to develop deep learning models with Keras.

4 hours

Zachary Deane-Mayer Headshot

Zachary Deane-Mayer

VP, Data Science at DataRobot

24
Python
Image Processing in Python

Learn to process, transform, and manipulate images at your will.

4 hours

Rebeca Gonzalez Headshot

Rebeca Gonzalez

Data Scientist, Hiberus Tecnologia

25
Python
Image Modeling with Keras

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

4 hours

Ariel Rokem Headshot

Ariel Rokem

Senior Data Scientist, University of Washington

26
Python
Hyperparameter Tuning in Python

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

4 hours

Alex Scriven Headshot

Alex Scriven

Senior Data Scientist @ Atlassian

27
Python
Introduction to PySpark

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

4 hours

Lore Dirick Headshot

Lore Dirick

Director of Data Science Education at Flatiron School

28
Python
Machine Learning with PySpark

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

4 hours

Andrew Collier Headshot

Andrew Collier

Data Scientist @ Exegetic Analytics

29
Python
Winning a Kaggle Competition in Python

Learn how to approach and win competitions on Kaggle.

4 hours

Yauhen Babakhin Headshot

Yauhen Babakhin

Kaggle Grandmaster

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Instructors

  • Hadrien Lacroix Headshot
    Hadrien LacroixCurriculum Manager at DataCampSee Hadrien Lacroix's Portfolio
  • Sara Billen Headshot
    Sara BillenData Scientist at DataCampSee Sara Billen's Portfolio
  • Lis Sulmont Headshot
    Lis SulmontContent Program Manager at DuolingoSee Lis Sulmont's Portfolio
  • Hugo Bowne-Anderson Headshot
    Hugo Bowne-AndersonData ScientistSee Hugo Bowne-Anderson's Portfolio

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