How to Become a Data Scientist

SF Data Science Meetup, June 30, 2014

- Transcript Header:
- How to Become a Data Scientist

- Transcript Body:

- 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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# How to Become a Data Scientist

How to Become a Data Scientist SF Data Science Meetup, June 30, 2014