A Data Science Curriculum

This is not intended to be mapped to a set of college courses. It is intended to be a listing of necessary skills for a data scientist. For a definition of data scientist, see this previous post.

Mathematics

Calculus – not directly important to data science, but the knowledge is important to understand the statistics and machine learning
Matrix Operations

Statistics

Regression – Linear and Logistic
Bayesian Statistics

Tools

Hadoop
R – stats
Octave – machine learning

Computing

Basic Programming – Java, C/C++, and Python seem to be good language choices
Machine Learning
Database Knowledge – not limited to just relational databases

Communication

Data Visualization – how to make data look good: maps, graphs, etc
Presentation – story telling, be comfortable explaining data to others
Writing

Do you have anything to add/remove from the list?

Originally Posted

April 14, 2012

Ryan Swanstrom

Last Modified:

November 11, 2020

Tags:

curriculum, data science, hadoop, machine learning, math, statistics

Comments

6 responses to “A Data Science Curriculum”

Craig

April 14, 2012

Also critical:
Business process design–How to design the info and data flows into and out of data systems.

Metadata and derived data design, computation, storage and retrieval.

Reply
1. Ryan Swanstrom
  
  April 18, 2012
  
  Good points. Being able to use and process the data is very important. Especially when real-time analysis is involved.
  
  Reply
David Diez

April 18, 2012

I enjoyed browsing the list! I’m putting Hadoop on my items of things to learn, and I’ve just started toying now with Octave.

Similar to what Craig said, data collection (experimental design / sampling) is a helpful topic in a curriculum and could be added.

Reply
1. Ryan Swanstrom
  
  April 18, 2012
  
  David,
  Hadoop is on my short list of things to learn as well. I hope to try some stuff out and post a bit to the blog. You will probably find Octave quite easy to pickup since you are very familiar with R. Octave is more like Matlab though.
  
  Reply
Ivan Brusic

April 25, 2012

Hadoop encompasses multiple subprojects nowadays. While understand the general concepts of Hadoop is important (MapReduce, clusters), working with a higher-level project such as Pig and Hive make the transition into Hadoop much easier.

Reply
1. Ryan Swanstrom
  
  April 25, 2012
  
  That is true. Thanks for sharing.
  
  Reply