You can a copy of the module timetable. The schedule has been colour coded to help you understand which parts of the course connect with the different parts of the coursework assessment.

  • Part A) Open health data and anonymisation

  • Part B) Algorithms and health data

  • Part C) Analyse and visualize results from a health data survey

  • Part D) Going further with programming

Week 1
2022-09-19 Overview of the module
2022-09-19 Introduction to RMarkdown
Week 2
2022-09-26 Healthcare Data: Open Data & Reproducibility
2022-09-26 Setting up reproducible data science with R
Week 3
2022-10-03 Data science with the tidyverse
2022-10-03 Exploratory Data Analysis with the tidyverse
Week 4
2022-10-10 Data visualisation
2022-10-10 Using factors to control data visualisations and Communicating with tables in R
Week 5
2022-10-17 Healthcare Data: Surveys
2022-10-17 Tidy Data: Wide vs Long Data
Week 6
2022-10-24 Data anonymisation
2022-10-24 Data anonymisation and Tidy Data: Surveys and separate()
Week 7
2022-10-31 Ethics in Algorithms
2022-10-31 Case studies of ethics in algorithms
Week 8
2022-11-07 Machine learning vs everything else
2022-11-07 Doing more with data visualisations
Week 9
2022-11-14 Regressions and correlations
2022-11-14 Tidyverse and regressions
Week 10
2022-11-21 Hypothesis Testing (and alternatives)
2022-11-21 Tidyverse and modelling
Week 11
2022-11-28 Why are we using code again?
2022-11-28 Programmatic solutions to doing many things
Week 12
2022-12-05 Assignment Q & A