We believe that building knowledge and skills in data science is essential for advancing neurodegeneration research. To support this mission, we have developed an introductory course in Computational Genetics and are actively working on developing new training materials tailored to the needs of our community. In the meantime, we also want to share outstanding learning resources from around the web, so that students, researchers, and clinicians can strengthen their data science skills and apply them to the challenges of understanding and treating tau-related diseases
Computational Genetics
This free introductory course explores the intersection of genetics and statistics through computational methods, with all materials openly available through our GitHub. Participants will gain a foundation in biological genetics while learning to use practical tools for working with large-scale genomic datasets. Designed to make complex data approachable, the course helps learners build the skills needed to analyze, interpret, and draw meaningful insights from genomic information.
The course is organized into three modules:
- Introduction to Computational Genetics
- Population Genetics
- Genetic Epidemiology.
Each module includes recorded lectures (available in both Spanish and English), coding exercises, and suggested readings, providing a comprehensive learning experience that combines theory with hands-on practice.
Artificial Intelligence for Science
Although we do not currently have our own developed course in this area, there are excellent free resources available to help learners explore how AI is transforming scientific research. These courses and materials provide both foundational knowledge and practical skills for applying machine learning and artificial intelligence to current research practices.
Courses:
Tau Consortium Bioinformatics Hub 