Difference between revisions of "BigDataChallenge2014"
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3) Free E-Learning from U of T – See attached PDF and the Access code is G70072789. There are a twelve different courses for students learn how to use SAS. | 3) Free E-Learning from U of T – See attached PDF and the Access code is G70072789. There are a twelve different courses for students learn how to use SAS. | ||
| − | 4) www.lexjansen.com – Great website for students to search and learn about different techniques of Analytics. | + | 4) http://www.lexjansen.com – Great website for students to search and learn about different techniques of Analytics. |
===Open Source resources=== | ===Open Source resources=== | ||
| − | 1) R | + | 1) R - Revolution R Open, from Revolution Analytics http://mran.revolutionanalytics.com/download/ |
| − | 2) Python | + | 2) Anaconda - a full-featured distribution of Python https://store.continuum.io/cshop/anaconda/ |
Revision as of 15:15, 17 October 2014
Link to the Big Data Challenge 2014 data set
BIG_DATA_CHLNG.xlsx
Computational tools and resources available to the students participating in the Challenge
SAS resources to be provided to students
1) SAS University Edition: http://www.sas.com/en_us/software/university-edition.html
2) SAS On-Demand For Academics – This is a free cloud version of 5 of our products including Enterprise Miner – our foundation Data Mining tool. I will start a course for the competition http://www.sas.com/govedu/edu/programs/od_academics.html
3) Free E-Learning from U of T – See attached PDF and the Access code is G70072789. There are a twelve different courses for students learn how to use SAS.
4) http://www.lexjansen.com – Great website for students to search and learn about different techniques of Analytics.
Open Source resources
1) R - Revolution R Open, from Revolution Analytics http://mran.revolutionanalytics.com/download/
2) Anaconda - a full-featured distribution of Python https://store.continuum.io/cshop/anaconda/