Overview
Unlock the power of data science to tackle climate and health challenges. This course spans environmental research using multi-omics, statistical techniques like regression and , and showcases real-world applications by public sector and non-profit actors. With engaging videos, interactive quizzes, and a case-based assignment, learners will gain both the knowledge and skills to drive impact.
You’ll explore real-world use cases like Khushi Baby’s climate-health dashboard in India and analyze District Health Information System 2 (DHIS2)’s climate-health toolkit through country-specific case studies from Africa and Asia. The course is free to access, and you’ll receive a certificate of completion upon completing all modules.
By the end of this course, you will be able to:
- Explain the urgency of climate-related health research.
- Identify how multi-omics can enhance climate research.
- Identify key statistical methods for analyzing genetic and environmental data. Including regression analysis, enrichment analysis, over-representation analysis, randomized clinical trials, causal inference and mendelian randomization.
- Understand how governments and nonprofits already use data in the social sector to tackle climate and health issues.
- Use the key statistical methods introduced in this course in your work.
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