Looking for the best courses to learn data science? This article covers the best Datacamp free courses for you to choose from.

Datacamp offers the best courses to learn data skills such as Python, SQL, R, and many more. While only 6 courses (out of 300+) are completely free, Datacamp offers a sneak peek at all its paid courses by giving away its first chapters for free.

To lessen the burden on your part, I have curated a list of all the free courses in Datacamp (including its paid courses for every category) in this article.

**List of All Datacamp Free Courses (Including Paid Courses)**

Datacamp Free Courses

Data Manipulation

Data Visualization

Reporting

Machine Learning

Probability & Statistics

Importing & Cleaning Data

Applied Finance

Programming

Others

Case Studies

Management

Data Engineering

If you’re planning to learn (or upgrade) your data science knowledge, the courses below will definitely help achieve your goal.

## Datacamp Free Courses

Machine Learning for Everyone

Data Science for Everyone

Data Engineering for Everyone

Introduction to Python

Introduction to SQL

Introduction to R

## Data Manipulation

Joining Data in SQL

Data Manipulation with pandas

Introduction to DAX in Power BI

Joining Data with pandas

Data Analysis in Excel

Data Manipulation with dplyr

Exploratory Data Analysis in SQL

PostgreSQL Summary Stats and Window Functions

Functions for Manipulating Data in PostgreSQL

Data Preparation in Power BI

Analyzing Police Activity with pandas

Joining Data with dplyr

DAX Functions in Power BI

Data Modeling in Power BI

Pivot Tables in Spreadsheets

Introduction to NumPy

Data Transformation in Power BI

Time Series Analysis in SQL Server

Manipulating Time Series Data in Python

Regular Expressions in Python

Introduction to Databases in Python

Intermediate Data Modeling in Power BI

Functions for Manipulating Data in SQL Server

Intermediate DAX in Power BI

Data Manipulation with data.table in R

Data Processing in Shell

Manipulating Time Series Data with xts and zoo in R

Working with Categorical Data in Python

Dealing with Missing Data in Python

Reshaping Data with pandas

Transactions and Error Handling in SQL Server

Data Visualization

Introduction to Power BI

Introduction to Tableau

Introduction to Data Visualization with Matplotlib

Introduction to Data Visualization with Seaborn

Data Visualization for Everyone

Data Visualization in Power BI

Introduction to Data Visualization with ggplot2

Intermediate Data Visualization with Seaborn

Analyzing Data in Tableau

Intermediate Data Visualization with ggplot2

Case Study: Analyzing Customer Churn in Power BI

Creating Dashboards in Tableau

Data Visualization in R

Data Visualization in Spreadsheets

Introduction to Data Visualization with Plotly in Python

User-Oriented Design in Power BI

Improving Your Data Visualizations in Python

Reports in Power BI

Reporting

Data Communication Concepts

Reporting with R Markdown

Analyzing Business Data in SQL

Reporting in SQL

Building Dashboards with shinydashboard

Case Studies: Building Web Applications with Shiny in R

Building Dashboards with flexdashboard

Machine Learning

Supervised Learning with scikit-learn

Advanced Deep Learning with Keras

Introduction to Deep Learning in Python

Unsupervised Learning in Python

Machine Learning with Tree-Based Models in Python

Introduction to Natural Language Processing in Python

Cluster Analysis in Python

Supervised Learning in R: Classification

Introduction to TensorFlow in Python

Image Processing in Python

Linear Classifiers in Python

Extreme Gradient Boosting with XGBoost

Machine Learning with scikit-learn

Machine Learning for Time Series Data in Python

Introduction to Deep Learning with Keras

Cluster Analysis in R

Preprocessing for Machine Learning in Python

Introduction to Deep Learning with PyTorch

Model Validation in Python

Image Processing with Keras in Python

Dimensionality Reduction in Python

Feature Engineering for Machine Learning in Python

Feature Engineering for NLP in Python

Machine Learning for Business

Sentiment Analysis in Python

Unsupervised Learning in R

Machine Learning with PySpark

Supervised Learning in R: Regression

AI Fundamentals

Hyperparameter Tuning in Python

Machine Learning with caret in R

ARIMA Models in Python

Advanced NLP with spaCy

Machine Learning for Finance in Python

Recurrent Neural Networks for Language Modeling in Python

Winning a Kaggle Competition in Python

Building Chatbots in Python

Introduction to Predictive Analytics in Python

Designing Machine Learning Workflows in Python

Building Recommendation Engines in Python

Probability & Statistics

Statistical Thinking in Python (Part 1)

Statistical Thinking in Python (Part 2)

Introduction to Statistics in R

Exploratory Data Analysis in Python

Introduction to Regression in R

Exploratory Data Analysis in R

Introduction to Statistics in Spreadsheets

Correlation and Regression in R

Time Series Analysis in Python

Introduction to Statistics in Python

Foundations of Probability in R

Intermediate Regression in R

Exploratory Data Analysis in Power BI

Hierarchical and Mixed Effects Models in R

Introduction to Linear Modeling in Python

Introduction to Statistics

Generalized Linear Models in R

Multiple and Logistic Regression in R

Customer Analytics and A/B Testing in Python

Hypothesis Testing in R

Introduction to Network Analysis in Python

Sampling in R

Time Series Analysis in R

Introduction to Regression with statsmodels in Python

Introduction to Statistical Modeling in R

Inference for Numerical Data in R

Forecasting in R

Importing & Cleaning Data

Introduction to Importing Data in Python

Cleaning Data in Python

Intermediate Importing Data in Python

Introduction to Importing Data in R

Streamlined Data Ingestion with pandas

Web Scraping in Python

Cleaning Data in R

Connecting Data in Tableau

Cleaning Data with PySpark

Intermediate Importing Data in R

Dealing With Missing Data in R

Creating PostgreSQL Databases

Web Scraping in R

Cleaning Data in PostgreSQL Databases

Cleaning Data in SQL Server Databases

Working with Web Data in R

Applied Finance

Introduction to Python for Finance

Introduction to R for Finance

Intermediate Python for Finance

Importing and Managing Financial Data in Python

Introduction to Financial Concepts in Python

Intermediate R for Finance

Financial Analytics in Spreadsheets

Introduction to Portfolio Risk Management in Python

Credit Risk Modeling in Python

Introduction to Portfolio Analysis in R

Financial Trading in Python

Introduction to Portfolio Analysis in Python

Intermediate Portfolio Analysis in R

Credit Risk Modeling in R

Quantitative Risk Management in Python

Quantitative Risk Management in R

Financial Modeling in Spreadsheets

GARCH Models in Python

Importing and Managing Financial Data in R

Financial Forecasting in Python

Bond Valuation and Analysis in R

Financial Trading in R

GARCH Models in R

Equity Valuation in R

Loan Amortization in Spreadsheets

Bond Valuation and Analysis in Python

Life Insurance Products Valuation in R

Options Trading in Spreadsheets

Programming

Introduction to Data Science in Python

Intermediate Python

Introduction to SQL Server

Intermediate SQL

Intermediate R

Python Data Science Toolbox (Part 1)

Python Data Science Toolbox (Part 2)

Introduction to the Tidyverse

Writing Efficient Python Code

Introduction to Relational Databases in SQL

Data Analysis in Spreadsheets

Writing Functions in Python

Introduction to PySpark

Object-Oriented Programming in Python

Introduction to Git

Introduction to Shell

Working with Dates and Times in Python

Intermediate SQL Server

Data Types for Data Science in Python

Introduction to Spreadsheets

Intermediate Spreadsheets

Others

RNA-Seq with Bioconductor in R

Introduction to Bioconductor in R

Differential Expression Analysis with limma in R

ChIP-seq with Bioconductor in R

Course Creation at DataCamp

Analyzing US Census Data in R

Case Studies

Case Study: Analyzing Job Market Data in Power BI

Case Study: School Budgeting with Machine Learning in Python

Applying SQL to Real-World Problems

Case Study: Analyzing Customer Churn in Tableau

Analyzing Marketing Campaigns with pandas

Data-Driven Decision Making in SQL

Case Study: Exploratory Data Analysis in R

Marketing Analytics in Spreadsheets

Marketing Analytics: Predicting Customer Churn in Python

Case Studies: Manipulating Time Series Data in R

Human Resources Analytics: Exploring Employee Data in R

Analyzing Election and Polling Data in R

Human Resources Analytics: Predicting Employee Churn in R

Analyzing US Census Data in Python

Management

Cloud Computing for Everyone

Data Science for Business

Data-Driven Decision Making for Business

Marketing Analytics for Business

Deploying and Maintaining Assets in Power BI

Data Engineering

Introduction to Data Engineering

Database Design

Introduction to Airflow in Python

AWS Cloud Concepts

ETL in Python

Building Data Engineering Pipelines in Python

NoSQL Concepts

Streaming Data with AWS Kinesis and Lambda

Streaming Concepts