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How to Become a Data Scientist
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How to Become a Data Scientist
Jul. 2, 2014•0 likes•197,077 views
640 likes
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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
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How to Become a Data Scientist
- Ryan Orban Co-Founder & CEO ryan@zipfianacademy.com @ryanorban
- Why are we talking about data science?
- Data Analyst Shortage Source: http://www.delphianalytics.net/wp-content/uploads/2013/04/GrowthOfDataVsDataAnalysts.png
- What is data science?
- Perfect Storm
- Technology Source: http://www.jcmit.com/diskprice.htm 0 1000 2000 3000 4000 1992 1997 2002 2007 2012 Capacity (GB) Cost per GB (USD)
- Unprecedented Data Growth
- Enter the Data Scientist
- What is Data Science? + Communication
- What do people look for in a data scientist?
- Broad-range generalist Deepexpertise T-Shaped Skillset
- T-Shaped Skillset Machine Learning, Statistics, Domain Knowledge Softw are EngineeringBusiness Acum en Distributed Com puting Com m unication
- Data Science Roles
- How to I become a data scientist?
- Data scientists need to know how to code.
- Python R Julia Java C++/GoScala/Clojure High-level Lower-level Learn to Code
- Learn to Code
- Data scientists need to be comfortable with mathematics & statistics.
- 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
- Mathematics & Statistics
- Data scientists need know machine learning & software engineering.
- 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)
- Open-Source Data Science Masters
- SlideRule
- DataTau
- Learning data science can be really hard.
- ≠ Data Science
- Learning data science can be really hard.
- Context is King
- It’s about putting the pieces together
- Pathways: MS/PhD in Data Science Internship Immersive Programs Self-study
- You don’t need a PhD to do data science.
- Backgrounds Educational Background BS MS PhD 0 4 8 12 16
- Backgrounds Disciplines Software Engineering Analysts Finance/Economics Engineering Physics Physical Sciences Mathematics Statistics Astronomy Linguistics Professional Poker 0 2 4 6 8
- Backgrounds 94% Placement Rate91% Placement $115k avg. salary
- 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
- Timeline STRUCTURED CURRICULUM HIRING DAY CAPSTONE PROJECT GRADUATION 1 8 11 12 INTERVIEW PREP Program Timeline
- Learning Techniques
- Hiring Partners
- ! • Working knowledge of programming • Background in a quantitative discipline • Comfortable with mathematics and statistics • Child-like curiosity What We Look For
- Zipfian Academy Data Science Immersive Data Fellowship Data Engineering Immersive Weekend Workshops
- 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 )
- The best way to learn data science is by doing data science.
- https://github.com/ipython/ipython/wiki/A-gallery-of- interesting-IPython-Notebooks
- Checklist: Learn the fundamentals Build out a project portfolio Apply! Blog about your experience
- A Practical Intro to Data Science http://bit.ly/learndatascience
- Thank You! Ryan Orban Co-Founder ryan@zipfianacademy.com @ryanorban
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