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
