SlideShare una empresa de Scribd logo
1 de 52
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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