Data Science Map
This is a wiki for learning the various skills that make a great data scientist.
There are lots of online courses relevant to "big data". Here are some:
http://bigdatauniversity.com/courses/
http://datascience101.wordpress.com/
Basics[edit | edit source]
One of the first questions we can ask is: What, exactly, IS Big Data
Another area of interest to many companies is Time Series Analysis
Road to becoming a data scientist[edit | edit source]
We start with "road to a data scientist" by Swami Chandrasekaran
Fundamentals[edit | edit source]
Statistics[edit | edit source]
Programming[edit | edit source]
Topics here include areas that are more directly related to the programming side of data science.
Machine Learning[edit | edit source]
Add specific sections in the future - for now, some useful resources:
http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=MachineLearning
Coursera Machine Learning Lecture Notes
Text Mining/NLP[edit | edit source]
Visualization[edit | edit source]
Big Data[edit | edit source]
Data Ingestion[edit | edit source]
Data Munging[edit | edit source]
Toolbox[edit | edit source]
MapReduce - originally the name for a proprietary implementation, now used more widely, especially in Hadoop
see http://johanlouwers.blogspot.com/2012/02/map-reduce-into-relation-of-big-data.html
Oracle Coherenece - An Oracle distributed Hash Map
Message Passing Interface - started in the early 90s, a way to program for parallel computers.
Julia - A high performance, open-source scientific programming language that uses a Just In Time compiler. The syntax is very Matlab-like.