The Course

This is a course on the fundamentals of data science.

Preamble

Overview

The course will be an enormous amount of work and cause you a large amount of stress. This is unfortunate, but there’s little way around it. All I can tell you is that having done this course, it’ll be easier in the future.

The purpose of this course is to develop students who appreciate, and can iterate on, the fundamentals of data science.

This course will require students to:

Essentially this course provides students with everything that they need to know to be able to do the most exciting thing in the world: use data to tell convincing stories.

FAQ

Pre-requisites

None.

Textbook

Alexander, 2022, Telling Stories with Data, CRC Press, https://www.tellingstorieswithdata.com.

Acknowledgements

Thank you to Monica Alexander.

Content

Week 1

‘Drinking from a fire hose’.

Week 2

‘Science-ing’.

Week 3

‘Communicating’.

Week 4

‘Gathering data’.

Week 5

‘Hunting data’.

Week 6

‘Cleaning data’.

Week 7

‘Store, retrieve, disseminate and protect’.

Week 8

‘Whoops, I forgot EDA’.

Week 9

‘IJALM - It’s Just A Linear Model’.

Week 10

‘Such a shame they’ll never meet’.

Week 11

‘Multilevel regression with post-stratification’.

Week 12

‘Lorem ipsum’.

Assessment

Summary

Item Weight (%) Due date
Weekly quiz 20 Weekly before the lecture
Professional conduct 1 Anytime during the teaching term
Paper 1 25 End of Week 3
Paper 2 25 End of Week 6
Paper 3 25 End of Week 9
Final Paper (initial submission) 1 End of Week 12
Final Paper (peer review) 3 Three days after that
Final Paper 25 Ten days after that

Weekly quizzes

Professional conduct

Paper #1

Paper #2

Paper #3

Final Paper