How to Become a Data Scientist
•
640 likes•197,820 views
How to Become a Data Scientist SF Data Science Meetup, June 30, 2014 Video of this talk is available here: https://www.youtube.com/watch?v=c52IOlnPw08 More information at: http://www.zipfianacademy.com Zipfian Academy @ Crowdflower
Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Viewers also liked (20)
Similar to How to Become a Data Scientist
Similar to How to Become a Data Scientist (20)
Recently uploaded
Recently uploaded (20)
How to Become a Data Scientist
- 2. Ryan Orban Co-Founder & CEO ryan@zipfianacademy.com @ryanorban
- 3. Why are we talking about data science?
- 4. Data Analyst Shortage Source: http://www.delphianalytics.net/wp-content/uploads/2013/04/GrowthOfDataVsDataAnalysts.png
- 5. What is data science?
- 8. Technology Source: http://www.jcmit.com/diskprice.htm 0 1000 2000 3000 4000 1992 1997 2002 2007 2012 Capacity (GB) Cost per GB (USD)
- 10. Enter the Data Scientist
- 11. What is Data Science? + Communication
- 12. What do people look for in a data scientist?
- 14. T-Shaped Skillset Machine Learning, Statistics, Domain Knowledge Softw are EngineeringBusiness Acum en Distributed Com puting Com m unication
- 16. How to I become a data scientist?
- 17. Data scientists need to know how to code.
- 18. Python R Julia Java C++/GoScala/Clojure High-level Lower-level Learn to Code
- 19. Learn to Code
- 20. Data scientists need to be comfortable with mathematics & statistics.
- 21. 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
- 23. Data scientists need know machine learning & software engineering.
- 24. 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)
- 25. Open-Source Data Science Masters
- 28. SlideRule
- 29. DataTau
- 30. Learning data science can be really hard.
- 32. ≠ Data Science
- 33. Learning data science can be really hard.
- 34. Context is King
- 35. It’s about putting the pieces together
- 36. Pathways: MS/PhD in Data Science Internship Immersive Programs Self-study
- 37. You don’t need a PhD to do data science.
- 38. Backgrounds Educational Background BS MS PhD 0 4 8 12 16
- 39. Backgrounds Disciplines Software Engineering Analysts Finance/Economics Engineering Physics Physical Sciences Mathematics Statistics Astronomy Linguistics Professional Poker 0 2 4 6 8
- 40. Backgrounds 94% Placement Rate91% Placement $115k avg. salary
- 41. 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
- 42. Timeline STRUCTURED CURRICULUM HIRING DAY CAPSTONE PROJECT GRADUATION 1 8 11 12 INTERVIEW PREP Program Timeline
- 44. Hiring Partners
- 45. ! • Working knowledge of programming • Background in a quantitative discipline • Comfortable with mathematics and statistics • Child-like curiosity What We Look For
- 46. Zipfian Academy Data Science Immersive Data Fellowship Data Engineering Immersive Weekend Workshops
- 47. 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 )
- 48. The best way to learn data science is by doing data science.
- 50. Checklist: Learn the fundamentals Build out a project portfolio Apply! Blog about your experience
- 51. A Practical Intro to Data Science http://bit.ly/learndatascience