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Submission + - Ask Slashdot: How to set up a big data/data science project portfolio? 1

An anonymous reader writes: I am a mid-career IT professional in the middle of a transition from IT to a domain within the biological sciences. My planned academic route to the target new domain will take at least 3-5 years to finish. In the interim, I want to work in (and earn from) the IT domain of Big Data/Data Science, since that is more aligned with the skills I need in my target new domain: data analysis, visualization, signal processing, imaging, simulation etc. The problem is that apart from early career stints, I've very little and only surface level experience with these topics. So I want to ask Slashdot for suggestions on the tasks Ive set myself to accomplish this transition. Specifically:
  1. What are the foundational topics I need to learn. What parts of math, statistics, machine learning, text analysis, scientific programming...?
  2. What books to read?
  3. What courses (preferably open/online) to take?
  4. I want to set up an online portfolio of big-data projects that I work on to showcase skills that I acquire in this domian. What are some of the more challenging, topical and novel applications areas and open problems to showcase in a portfolio, such that it is distinctive and interesting. E.g., consumer behavior, neuro-/bio-informatics, socio-economic trends ...
  5. How do I find sources of open/non-propreitary data sets to use for my portfolio projects?
  6. What hosting resources do I need to set up a portfolio of big-data projects? Any suggestions on specific hosting providers?
  7. What tools should I strive to learn (preferably FOSS): E.g., Hadoop, R, Octave, Python ...?
  8. What are the industry and trade bodies that cater to big-data professionals?
  9. How do I acquire mentor(s)/guide(s) who can informally guide me through the above skill acquisition and portfolio creation tasks?
  10. Any othe Data Science related wisdom
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Ask Slashdot: How to set up a big data/data science project portfolio?

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  • I'm in Computational Biology, and I'd say that the most valuable skills you should learn (and the ones most often seen in this field) are more mathematical and/or statistical than "big data." Understanding how to properly normalize your data or calculate a p-value will take you much further than being able to spin up a 100-node Hadoop instance in most labs.

    I think you should spend the first year on your home PC. Download RStudio and work through a few R Tutorials, then find some data/questions that intere

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