Comments

9 responses to “Data Scientist: Consider the Curriculum”

1. 

   srisreedhar

   February 25, 2013

   Mechanistic Analysis

   Reply
   1. 

      Ryan Swanstrom

      February 25, 2013

      Thanks for the comment. I am not even familiar with the topic. I will have to google it and read up about it.

      Thanks,
      Ryan

      Reply
2. Required Knowledge for a Data Scientist | Bayes Craze

   February 26, 2013

   […] 101, by Ryan Swanstrom, a great resource for budding data scientists like me, recently posted a must-read list of all the concepts a data scientist should know. Here’s the list he came up […]

   Reply
3. 

   Ahmad Baubaid

   February 26, 2013

   Nice post !

   I’m not entirely familiar with everything written in this post, but I have a feeling that some of the topics are parts of other topics in the list.

   e.g. Shouldn’t “Unsupervised Learning” be part of “Machine Learning” ? Maybe the same thing for “Linear and Logistic Learning” which is a part of Statistics/Machine Learning.

   So, I’m wondering, if we group and cluster the topics you’ve listed, what major topics would be in that list that would comprehend all others.

   Reply
   1. 

      Ryan Swanstrom

      February 26, 2013

      Ahmad,
      That is good point, but I also think it is also beneficial to know the exact topics and not just the broad categories. Anyhow, the list is a good goal to shoot for.

      Thanks for commenting.
      Ryan

      Reply
4. 

   A Data Head’s Diary

   February 26, 2013

   Reblogged this on A Data Head's Diary and commented:
   This is great checklist of topics to become proficient in for all aspiring Data Scientists. This list of skills can reasonably be attained within a master’s degree program in Statistics, Computer Science or Operations Research.

   Reply
5. 

   A Data Explorer

   March 28, 2013

   What strikes me is this curriculum only consists of courses on actual data analysis techniques/methods. Does this imply that a data analyst should not have some domain knowledge? (which is something different from being a domain expert!)

   Reply
   1. 

      Ryan Swanstrom

      March 28, 2013

      I am not sure if you are talking about my post or the original article. My post does list just the data analysis methods. The original article mentions an “Applications and outcomes” section that briefly covers domain knowledge. However, a lot of domain knowledge is difficult to cover in a classroom curriculum. I do think that domain knowledge is important to a good data scientist.

      Reply
6. Restoration of defocused and blurred images. | 3D Tech @ 3d.coldstreams.com

   April 7, 2013

   […] Data Scientist: Consider the Curriculum […]

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