The Best Data Science Curriculum

Our top three course picks for each major subject (in terms of course quantity) within data science are listed below:

Intro to Programming

Learn to Program: The Fundamentals (LPT1) and Crafting Quality Code (LPT2) by the University of Toronto via Coursera

An Introduction to Interactive Programming in Python (Part 1) and (Part 2) by Rice University via Coursera

R Programming Track by DataCamp

Statistics & Probability

Foundations of Data Analysis – Part 1: Statistics Using R and Part 2: Inferential Statistics by the University of Texas at Austin via edX

Statistics with R Specialization by Duke University via Coursera

Introduction to Probability – The Science of Uncertainty by the Massachusetts Institute of Technology (MIT) via edX

Intro to Data Science

Data Science A-Z™: Real-Life Data Science Exercises Included by Kirill Eremenko via Udemy

Intro to Data Analysis by Udacity

Data Science Fundamentals by Big Data University

Data Visualization

Data Visualization with Tableau Specialization by the University of California, Davis via Coursera

Data Visualization with ggplot2 by DataCamp

Tableau 10 Series (Tableau 10 A-Z and Tableau 10 Advanced Training) by Kirill Eremenko and the SuperDataScience Team on Udemy

Machine Learning

Machine Learning by Stanford University via Coursera

Machine Learning by Columbia University via edX

Machine Learning A-Z™: Hands-On Python & R In Data Science by Kirill Eremenko and Hadelin de Ponteves via Udemy

Deep Learning

Creative Applications of Deep Learning with TensorFlow by Kadenze

Neural Networks for Machine Learning by the University of Toronto via Coursera

Deep Learning A-Z™: Hands-On Artificial Neural Networks by Kirill Eremenko and Hadelin de Ponteves via Udemy

Our top course pick for each of the smaller subjects (in terms of course quantity) within data science are listed below:

Python and its tools

Python Programming Track by DataCamp, plus their individual pandas courses:

pandas Foundations
Manipulating DataFrames with pandas
Merging DataFrames with pandas
R and its tools

R Programming Track by DataCamp, plus their individual dplyr and data.table courses:

Data Manipulation in R with dplyr
Joining Data in R with dplyr
Data Analysis in R, the data.table Way
Databases & SQL

Introduction to Databases by Stanford University via Stanford OpenEdx (note: reviews from the deprecated version on Coursera)
Data Preparation

Importing & Cleaning Data with Python Track by DataCamp
Importing & Cleaning Data with R Track by DataCamp

Exploratory Data Analysis

Data Analysis with R by Udacity and Facebook
Big Data

The Ultimate Hands-On Hadoop – Tame your Big Data! by Frank Kane via Udemy, then if you want more on specific tools (all by Frank Kane via Udemy):
Taming Big Data with Apache Spark and Python – Hands On!
Taming Big Data with MapReduce and Hadoop – Hands On!
Apache Spark 2.0 with Scala – Hands On with Big Data!
Taming Big Data with Spark Streaming and Scala – Hands On!

Software Skills

Software Testing by Udacity
Software Debugging by Udacity
Version Control with Git and GitHub & Collaboration by Udacity (updates to Udacity’s popular How to Use Git & GitHub course)


Building a Data Science Team by Johns Hopkins University via Coursera
Learning How to Learn: Powerful mental tools to help you master tough subjectsby University of California, San Diego via Coursera
Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potentialby McMaster University via Coursera

Table of Contents

Why You Should Trust Us
About the Data Science Career Guide
How We Picked Courses to Consider
How We Tested
Our Picks
Intro to Programming
Statistics & Probability
Intro to Data Science
Data Visualization
Machine Learning
Deep Learning
Python & Its Tools
R & Its Tools
Data Preparation
Exploratory Data Analysis
Databases & SQL
Big Data
Software Skills
The Future of This Guide
My Future
About Class Central Career Guides
Author Bio