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Intro	
  slide	
  
Data Science Education at
Teaching
 Blogging
 Research
Teaching
 Blogging
 Research
jhudatascience.org
Teaching
 Blogging
 Research
simplystatistics.org
@simplystats
Teaching
 Blogging
 Research
jtleek.com
 
	
  
Teaching hands on
data analysis
“Here is a 
monograph on
GLMMs.”
+
-
Github
Data cleaning
Machine learning
Reproducibility
Data Analysis

 Special cases
Some asymptotics
Some mathematical...
Your project is to quantify the level of
collaborative and methodological work
performed by the tenure-track faculty at
th...
1st
Discussion Point: 
To add data analysis you
have to subtract something
else.
How we get into MOOCs
every letter is negotiable, from Wikipedia citing Mathieu Plord
from: jtleek@gmail.com
Roger let me know you gave him a
ballpark figure for the number of
students registered for his cour...
from: pangwei@coursera.org
Hi Jeff,
7,000 students! It's pretty awesome.
(You'll be able to check this out
yourself next w...
from: rdpeng@gmail.com
You are f**ed.
-roger
	
  
A MOOC is

Videos
A MOOC is

Quizzes
A MOOC is

Forums
A MOOC is

Peer grading
6503
Data analysis
completers
6761*
M.S. in
Statistics
*	
  h.p://community.amstat.org/blogs/steve-­‐pierson/2014/02/09/la...
 
	
  
Data Science
Specialization
9 classes
1 month long
Every month
Less standard content
Standard content
Github
Data cleaning
Interactive graphics
Presentations
Capstone

Probability
Infer...
The Team
Cumulative Enrollment
2nd
 
Discussion Point: 
What opportunities are 
there at “medium scale”?
JHU DSS Collaborations
Instant hands on data science
Lectures
Course materials
Automated Grading
Instructor Dashboards
Vir...
jtleek.com/talks
1.  Data analysis è ? in
curriculum

2. Opportunities at
medium scale
Data Science Education at JHSPH
Data Science Education at JHSPH
Data Science Education at JHSPH
Data Science Education at JHSPH
Data Science Education at JHSPH
Data Science Education at JHSPH
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Data Science Education at JHSPH

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A talk about JHU Data Science Initiatives given at JSM 2014.

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Data Science Education at JHSPH

  1. 1. Intro  slide   Data Science Education at
  2. 2. Teaching Blogging Research
  3. 3. Teaching Blogging Research jhudatascience.org
  4. 4. Teaching Blogging Research simplystatistics.org @simplystats
  5. 5. Teaching Blogging Research jtleek.com
  6. 6.     Teaching hands on data analysis
  7. 7. “Here is a monograph on GLMMs.”
  8. 8. + - Github Data cleaning Machine learning Reproducibility Data Analysis Special cases Some asymptotics Some mathematical details
  9. 9. Your project is to quantify the level of collaborative and methodological work performed by the tenure-track faculty at the following departments: •  Johns Hopkins Biostatistics •  University of Washington Biostatistics •  University of Minnesota Biostatistics •  Stanford Statistics •  Iowa State Statistics •  University of Chicago Statistics
  10. 10. 1st Discussion Point: To add data analysis you have to subtract something else.
  11. 11. How we get into MOOCs
  12. 12. every letter is negotiable, from Wikipedia citing Mathieu Plord
  13. 13. from: jtleek@gmail.com Roger let me know you gave him a ballpark figure for the number of students registered for his course "Computing for Data Analysis”. Could you give me an idea of how many have registered for my course "Data Analysis?”  
  14. 14. from: pangwei@coursera.org Hi Jeff, 7,000 students! It's pretty awesome. (You'll be able to check this out yourself next week, once the class sites are up.)  
  15. 15. from: rdpeng@gmail.com You are f**ed. -roger  
  16. 16. A MOOC is Videos
  17. 17. A MOOC is Quizzes
  18. 18. A MOOC is Forums
  19. 19. A MOOC is Peer grading
  20. 20. 6503 Data analysis completers 6761* M.S. in Statistics *  h.p://community.amstat.org/blogs/steve-­‐pierson/2014/02/09/largest-­‐graduate-­‐programs-­‐in-­‐staAsAcs  
  21. 21.     Data Science Specialization
  22. 22. 9 classes 1 month long Every month
  23. 23. Less standard content Standard content Github Data cleaning Interactive graphics Presentations Capstone Probability Inference Regression and GLMs EDA
  24. 24. The Team
  25. 25. Cumulative Enrollment
  26. 26. 2nd Discussion Point: What opportunities are there at “medium scale”?
  27. 27. JHU DSS Collaborations Instant hands on data science Lectures Course materials Automated Grading Instructor Dashboards Virtual TAs
  28. 28. jtleek.com/talks 1.  Data analysis è ? in curriculum 2. Opportunities at medium scale

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