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How to Become a Data Scientist

Jul. 2, 2014
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How to Become a Data Scientist

  1. Ryan Orban Co-Founder & CEO ryan@zipfianacademy.com @ryanorban
  2. Why are we talking about data science?
  3. Data Analyst Shortage Source: http://www.delphianalytics.net/wp-content/uploads/2013/04/GrowthOfDataVsDataAnalysts.png
  4. What is data science?
  5. Perfect Storm
  6. Technology Source: http://www.jcmit.com/diskprice.htm 0 1000 2000 3000 4000 1992 1997 2002 2007 2012 Capacity (GB) Cost per GB (USD)
  7. Unprecedented Data Growth
  8. Enter the Data Scientist
  9. What is Data Science? + Communication
  10. What do people look for in a data scientist?
  11. Broad-range generalist Deepexpertise T-Shaped Skillset
  12. T-Shaped Skillset Machine Learning, Statistics, Domain Knowledge Softw are EngineeringBusiness Acum en Distributed Com puting Com m unication
  13. Data Science Roles
  14. How to I become a data scientist?
  15. Data scientists need to know how to code.
  16. Python R Julia Java C++/GoScala/Clojure High-level Lower-level Learn to Code
  17. Learn to Code
  18. Data scientists need to be comfortable with mathematics & statistics.
  19. Mathematics Statistical Analysis Mathematics & Statistics Distributions (Binomial, Poisson, etc.) Summary Statistics (Mean, Variance, etc.) Hypothesis Testing Bayesian Analysis Linear Algebra (Matrix Factorization) Calculus (Integrals, Derivatives, etc) Graph Theory Probability/ Combinatorics
  20. Mathematics & Statistics
  21. Data scientists need know machine learning & software engineering.
  22. Distributed Computing Supervised (SVM, Random Forest) NLP / Information Retrieval Algorithms & Data Structures Data Visualization Data Munging Machine Learning & Software Engineering Machine Learning Software Engineering Validation, Model Comparison Unsupervised (K-means, LDA)
  23. Open-Source Data Science Masters
  24. SlideRule
  25. DataTau
  26. Learning data science can be really hard.
  27. ≠ Data Science
  28. Learning data science can be really hard.
  29. Context is King
  30. It’s about putting the pieces together
  31. Pathways: MS/PhD in Data Science Internship Immersive Programs Self-study
  32. You don’t need a PhD to do data science.
  33. Backgrounds Educational Background BS MS PhD 0 4 8 12 16
  34. Backgrounds Disciplines Software Engineering Analysts Finance/Economics Engineering Physics Physical Sciences Mathematics Statistics Astronomy Linguistics Professional Poker 0 2 4 6 8
  35. Backgrounds 94% Placement Rate91% Placement $115k avg. salary
  36. The Program • 12-week immersive bootcamp in San Francisco • Project-based curriculum with real datasets, solving actual problems • Guest lectures from leaders in the field • Personal mentorship to help students grow
  37. Timeline STRUCTURED CURRICULUM HIRING DAY CAPSTONE PROJECT GRADUATION 1 8 11 12 INTERVIEW PREP Program Timeline
  38. Learning Techniques
  39. Hiring Partners
  40. ! • Working knowledge of programming • Background in a quantitative discipline • Comfortable with mathematics and statistics • Child-like curiosity What We Look For
  41. Zipfian Academy Data Science Immersive Data Fellowship Data Engineering Immersive Weekend Workshops
  42. Zipfian Academy @ZipfianAcademy Data Science Immersive 12-weeks (Sep 8th) Weekend Workshops http://zipfianacademy.com/apply http://zipfianacademy.com/workshops Next: Interactive Visualizations w/ d3.js ( July 19 )
  43. The best way to learn data science is by doing data science.
  44. https://github.com/ipython/ipython/wiki/A-gallery-of- interesting-IPython-Notebooks
  45. Checklist: Learn the fundamentals Build out a project portfolio Apply! Blog about your experience
  46. A Practical Intro to Data Science http://bit.ly/learndatascience
  47. Thank You! Ryan Orban Co-Founder ryan@zipfianacademy.com @ryanorban
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