Data Science at JHSPH - Speaker Deck

Slide 1

Slide 1 text

Intro slide Data Science Education at

Slide 2

Slide 2 text

Teaching Blogging Research

Slide 3

Slide 3 text

Teaching Blogging Research jhudatascience.org

Slide 4

Slide 4 text

Teaching Blogging Research simplystatistics.org @simplystats

Slide 5

Slide 5 text

Teaching Blogging Research jtleek.com

Slide 6

Slide 6 text

Teaching hands on data analysis

Slide 7

Slide 7 text

“Here is a monograph on GLMMs.”

Slide 8

Slide 8 text

No content

Slide 9

Slide 9 text

+ - Github Data cleaning Machine learning Reproducibility Data Analysis Special cases Some asymptotics Some mathematical details

Slide 10

Slide 10 text

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

Slide 11

Slide 11 text

No content

Slide 12

Slide 12 text

1st Discussion Point: To add data analysis you have to subtract something else.

Slide 13

Slide 13 text

How we get into MOOCs

Slide 14

Slide 14 text

every letter is negotiable, from Wikipedia citing Mathieu Plord

Slide 15

Slide 15 text

No content

Slide 16

Slide 16 text

from: [email protected] 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?”

Slide 17

Slide 17 text

from: [email protected] 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.)

Slide 18

Slide 18 text

from: [email protected] You are f**ed. -roger

Slide 19

Slide 19 text

A MOOC is Videos

Slide 20

Slide 20 text

A MOOC is Quizzes

Slide 21

Slide 21 text

A MOOC is Forums

Slide 22

Slide 22 text

A MOOC is Peer grading

Slide 23

Slide 23 text

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

Slide 24

Slide 24 text

Data Science Specialization

Slide 25

Slide 25 text

9 classes 1 month long Every month

Slide 26

Slide 26 text

Less standard content Standard content Github Data cleaning Interactive graphics Presentations Capstone Probability Inference Regression and GLMs EDA

Slide 27

Slide 27 text

The Team

Slide 28

Slide 28 text

Cumulative Enrollment

Slide 29

Slide 29 text

2nd Discussion Point: What opportunities are there at “medium scale”?

Slide 30

Slide 30 text

No content

Slide 31

Slide 31 text

No content

Slide 32

Slide 32 text

No content

Slide 33

Slide 33 text

JHU DSS Collaborations Instant hands on data science Lectures Course materials Automated Grading Instructor Dashboards Virtual TAs

Slide 34

Slide 34 text

jtleek.com/talks 1.  Data analysis è ? in curriculum 2. Opportunities at medium scale