Appendix C β Technical resources for intermediate to advanced data scientists
C.1 R programming
C.1.1 Tidyverse
 |
tidyverse | Collection of R packages designed for data science |
| Link | Recommendation |
|---|---|
| Introduction to the Tidyverse (JHU Data Science Labβs lectures) | β β β β β |
| Importing data in the Tidyverse (JHU Data Science Labβs lectures) | β β β β β |
| Wranging data in the Tidyverse | |
| Visualizing data in the Tidyverse | |
| Modeling Data in the Tidyverse |
| Link | |
|---|---|
| Advanced R Programming | |
| Building R packages | |
| Building Data Visualization Tools | |
| Advanced R and solutions |
C.1.2 Spatial analyses
| Link | Recommendation |
|---|---|
| afrimapr - mapping data in Africa |
C.1.3 Literature reviews
| metaverse | Collection of R packages designed for data science | |
| litsearchr | Excellent R package for supporting evidence synthesis generation |
There are very well documented) vignettes/tutorials
- https://luketudge.github.io/litsearchr-tutorial/litsearchr_tutorial.html
- https://elizagrames.github.io/litsearchr/litsearchr_vignette.html
- https://elizagrames.github.io/litsearchr/introduction_vignette_v010.html
C.1.4 Multilanguage programming
| Link | Language | Recommendation |
|---|---|---|
| Harvard Data Science workshops materials | R, Python, Stata |
C.1.5 Machine learning
| MOOC | Language | Recommendation |
|---|---|---|
| Machine learning in Python with scikit-learn | Python | β β β β β |
| Machine learning for healthcare |
Supervised Machine Learning for Text Analysis in R
https://ocw.mit.edu/courses/6-0002-introduction-to-computational-thinking-and-data-science-fall-2016/
https://ocw.mit.edu/courses/6-438-algorithms-for-inference-fall-2014/
C.1.6 Comprehensive lectures
| Link | Tools | Recommendation | Pricing |
|---|---|---|---|
| Principles, Statistical and Computational Tools for Reproducible Data Science | R and Rstudio Python, Git, and GitHub |
|
|
| Collaborative Data Science for Healthcare | Experience with R, Python and/or SQL is required |
|
|
| https://www.coursera.org/learn/data-public-health | |||
C.2 Data collection workflows
|
ruODK | |
| sitrep | ||
| REDCap+R | ||
| REDCapTidieR |
C.2.1 Python programming
C.3 Books and websites
C.3.1 Git and GitHub
| Link | Recommendation |
|---|---|
| GitHub Guides | |
| Happy Git and GitHub for the useR |
C.3.2 Reproducible research
- The Turing way (1) β β β β β
| Link | Language | Recommendation |
|---|---|---|
| R for applied epidemiology and public health (2) | R | β β β β β |
| R for Epidemiology | R | |
| R4epis | R | |
| R for Data Science | R | β β β β β |
| Quarto for scientists | R | |
| Tidyverse Skills for Data Science (jhudatascience.org) | R |
C.4 Communities
Conferences
https://www.r-project.org/conferences/ in general in June-July Fees for Tanzanian participants around 6 USD / person
C.5 Statistics
https://rmisstastic.netlify.app/
| grf |
C.6 Quarto
Styling PDF documents with Quarto extensions - April 2024
Resource from Nicola Rennie