Mini-projects for the residential training. As part of the Eneza Residential training 2024, you will collaboratively work on mini-projects in groups of at between 4 and 6.
- Project 1: Impact of Data Preprocessing on Machine Learning from a Diabetes Dataset
- Project 2: Open Data in Health in Kenya: What is available?
- Project 3: Role of sylvatic transmission in the AAT of livestock in Shimba Hills.
- Project 4: Data mining to understand the adoption of Data Science for Health in Kenya
- Project 5: Utilizing machine learning for attributing sources of foodborn pathogens
- Project 6: Biological age prediction using routine laboratory test results in a cohort of healthy adults in sub-Saharan Africa
To select a project, please comment on the issue and why you'd like to tackle the mini-project. Select at least two, and specify your First, Second and Third choice.
- Work collaboratively on the project. In your report, you need to state the role played by each group member.
- Collaborate via Git & GitHub, making use of the Git Workflow.
- Assign tasks to group members using GitHub issues and learn from each other. Every group member must be knowledgeable of the whole group's work.
- A reproducible workflow, Jupyter Notebooks, or Rmarkdown notebooks, together with computational environment should accompany your submission.
- Document your scripts in a nice and informative way. Your scripts, programs, workflows, etc, will be reviewed as a critical part of the project assessment.
- Your writeup should be complete with visualizations.