Data Science at JHSPH

A talk describing some of Jeff's work on data science education at Hopkins.

Transcript

1. Intro  slide   Data Science Education at
2. Teaching Blogging Research
3. Teaching Blogging Research jhudatascience.org
4. Teaching Blogging Research simplystatistics.org @simplystats
5. Teaching Blogging Research jtleek.com
6.     Teaching hands on data analysis
7. “Here is a monograph on GLMMs.”
9. + - Github Data cleaning Machine learning Reproducibility Data Analysis Special cases Some asymptotics Some mathematical details
10. 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
12. 1st Discussion Point: To add data analysis you have to subtract something else.
13. How we get into MOOCs
14. every letter is negotiable, from Wikipedia citing Mathieu Plord
16. 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?”  
17. 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.)  
18. from: rdpeng@gmail.com You are f**ed. -roger  
19. A MOOC is Videos
20. A MOOC is Quizzes
21. A MOOC is Forums
22. A MOOC is Peer grading
23. 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  
24.     Data Science Specialization
25. 9 classes 1 month long Every month
26. Less standard content Standard content Github Data cleaning Interactive graphics Presentations Capstone Probability Inference Regression and GLMs EDA
27. The Team
28. Cumulative Enrollment
29. 2nd Discussion Point: What opportunities are there at “medium scale”?
33. JHU DSS Collaborations Instant hands on data science Lectures Course materials Automated Grading Instructor Dashboards Virtual TAs
34. jtleek.com/talks 1.  Data analysis è ? in curriculum 2. Opportunities at medium scale