1.
Data Science
Introduction
Gang Tao

2.
What is Data Science

3.
Data Science Flow

4.
Statistics and
Probability

5.
Admit Gender Dept Freq
Admi.ed Male A 512
Rejected Male A 313
Admi.ed Female A 89
Rejected Female A 19
Admi.ed Male B 353
Rejected Male B 207
Admi.ed Female B 17
Rejected Female B 8
Admi.ed Male C 120
Rejected Male C 205
Admi.ed Female C 202
Rejected Female C 391
Admi.ed Male D 138
Rejected Male D 279
Admi.ed Female D 131
Rejected Female D 244
Admi.ed Male E 53
Rejected Male E 138
Admi.ed Female E 94
Rejected Female E 299
Admi.ed Male F 22
Rejected Male F 351
Admi.ed Female F 24
Rejected Female F 317
56%
44%
acceptec rejected
65%
35%
Men
Women

6.
Simpsons Paradox

7.
45%
16%
18%
11%

8.
Machine Learning

9.
Data Mining or
Machine Learning

10.
Key Tools
• Classification
• Regression
• Cluster
• Data Reduction

11.
Classification and Regression

12.
Cluster

13.
Data Reduction

14.
Process of ML

15.
Understand Data

16.
Data Scientist

17.
What is Data Scientist
• Know which question to ask
• Understand the data
• Know how to interpret the data
• Works in a team

18.
How to become a data
scientist ?

19.
Data is Tricky