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)
Miscellaneous
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
Miscellaneous
The Future of This Guide
My Future
About Class Central Career Guides
Author Bio
Via class-central
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