Data Science and AI in Context

1

Introduction

00:00 • 3min

2

What's the Origin Story Behind the Book on Data Science?

02:59 • 3min

3

Is This a Good Book for Product Managers?

05:40 • 2min

4

The Analysis Rubric for Data Science Projects

07:41 • 3min

5

The Best Way to Operationalize a Data Science Rubric?

10:47 • 5min

6

Injecting Software Engineering Rigorousness Into Data Science?

15:30 • 2min

7

Can We Get a Good Result?

17:29 • 2min

8

Do You Have the Right Objective Function?

19:04 • 3min

9

Is There a Rubric for Data and Analytics?

21:48 • 2min

10

Getting Students Excited About Data Science Topics

23:40 • 2min

11

Machine Learning - What's Next?

25:21 • 3min

12

Is the Trend Towards Synthetic Data Also Getting Automated?

28:17 • 2min

13

Is There a Risk in the Python Software Supply Chain?

30:22 • 4min

14

Is There a Future for Open Source Language Models?

34:49 • 2min

15

Is There a Tradeoff Between Convenience and Control?

36:36 • 2min

16

What Do Data Scientists Need to Know in Five Years?

38:28 • 2min

17

Is It Calculus?

40:26 • 4min

18

How Much Coding Will Software Engineers Still Be Doing?

43:57 • 2min

19

Data Science and Context - A Must Read Book

45:58 • 2min