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COURSE SEQUENCE:

Public Health Data Analyst

📊 From Beginner to Proficient Analyst

Supported by the Data Science Catalytic Fund at the Global Fund, this five-course sequence will build up your expertise in data analysis for epidemiology.

By the end, you will be able to:

  • Wrangle and analyze health data in R
  • Create reproducible documents and dashboards with RMarkdown
  • Visualize geographic and time trends for diseases like HIV, tuberculosis, and malaria
  • Automate workflows for data processing and visualization
  • Communicate public health insights with effective data reports

👨‍💻 Who the Courses are for

All health professionals, students, researchers and policy-makers looking to build skills for epidemiological data analysis and reporting.

The sequence is developed for beginners, but those already experienced with R may jump to the “Further Data Analysis with R” course, where more advanced content begins, including HIV, TB and Malaria epidemiological analyses.

 

Course Sequence

Completion Time

3-5 weeks per course (assuming 10 hrs study per week)

Funders & Partners

We are grateful to the following organizations for their support.

Courses

The courses below combine rich videos, interactive quizzes, and practical assignments to build health data science expertise.

R FOUNDATIONS

Get started learning the best language for data analysis. Learn the basics of R, RStudio, Rmarkdown and data importing. 

ESTIMATED TIME TO COMPLETE:  3 weeks (10 HRS OF WORK PER WEEK)

DATA UNTANGLED

Learn to manipulate data using the dplyr package. Filter, mutate, group and summarize your data to extract insights and prepare for downstream analysis.

ESTIMATED TIME TO COMPLETE:  4 WEEKS

DATA ON DISPLAY

Master the most popular data visualization package in R. Create stunning visualizations of your data using ggplot2.

ESTIMATED TIME TO COMPLETE:  3 WEEKS

DIVE DEEPER

Work with dates, strings, factors, joins, loops, and functions to wrangle complex epidemiological data into impactful public health insights.

ESTIMATED TIME TO COMPLETE:  5 WEEKS

APPLIED R FOR EPI

Polish your R skills for epi analysis and communication with application to HIV, TB, and malaria data – visualize demographics, geospatial patterns and temporal trends in reproducible reports.

ESTIMATED TIME TO COMPLETE:  3 WEEKS

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