http://ocw.mit.edu/index.htm
The list of courses is here 
http://ocw.mit.edu/courses/index.htm
Something every one should know and use.

http://ocw.mit.edu/index.htm
The list of courses is here
http://ocw.mit.edu/courses/index.htm
Something every one should know and use.

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Few other resources for learning data analytics

Here are some general resources that you may find useful for a further study.  This list is by no means complete.  We welcome additional suggestions through the appropriate discussion thread.

Some other on-line classes and tutorials in this arena:

General e-Science / Data Science resources:

Books on Data Mining and Machine Learning:

  • “Data Mining – Concepts and Techniques”, J. Han & M. Kamber, MK
  • “Neural Networks for Pattern Recognition”, C.M. Bishop, Oxford University Press
  • “Pattern Recognition and Machine Learning”, C.M. Bishop
  • “The Elements of Statistical Learning”, T. Hastie, R. Tibshirani J. Friedman, 2009, free download
  • “Introduction to Information Retrieval”, Christopher D. Manning, Prabhakar Raghavan & Hinrich Schütze, 2008, Cambridge University Press
  • “Gaussian Processes for Machine Learning”, Carl Edward Rasmussen and Christopher K. I. Williams, The MIT Press, 2006: free download
  • Tika in Action“, Mattmann & Zitting, Manning Publications, 2011, 256 pages.

Web Services and standalone applications:

Programming Languages and DM Libraries:

 

Do You Want to Learn About Learning Analytics? #dalmooc

techKNOWtools

Last week, I attended the UTA LINK Lab talk presented by Dragan Gasevic (@dgasevic) on learning analytics and research. This discussion shared all the digital traces and learning that can be collected and measured in our various learning environments, and questions how we are best doing some of these analytics within our institutions. Although we have a number of statistics, data, and information on our learners – how can we offer actionable insight, summative feedback, and information about learner progress. Our post-secondary institutions seem to want to only deal with the “R” word = Retention. Often institutions are looking to identify students at risk, provide information about learning success, and understand how to enhance learning – but how can we effectively use data when often times our metrics only focus on single outcomes?

data-analytics-608x211

Photo c/o the #dalmooc edX Course Site

Instead, it is the process and context that our education institutions need…

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