Machine Learning for Evolutionary Genomics (MLEG01) – Applications for Marine Mammal Research
https://prstats.org/course/machine-learning-for-evolutionary-genomics-mleg01/

Delivered by experienced computational biologists, evolutionary geneticists, and machine learning researchers.

Learn how to apply Machine Learning (ML) and Artificial Intelligence (AI) methods to genomic data, with techniques that are increasingly relevant across marine mammal research and conservation genetics.

As genomic datasets continue to grow in size and complexity, machine learning is becoming an important tool for identifying patterns that are difficult to detect using traditional statistical approaches. While this course focuses on evolutionary genomics, the methods taught are highly transferable to marine mammal research, including population structure analysis, conservation genetics, adaptation, demographic history, and genomic monitoring.

What you’ll gain

• A strong understanding of machine learning concepts in genomics and evolutionary biology
• Practical experience applying machine learning methods to genomic datasets
• Skills in predictive modelling, classification, and pattern recognition
• Understanding of supervised and unsupervised learning approaches
• Ability to evaluate model performance and avoid common pitfalls
• Confidence in interpreting machine learning outputs in biological contexts

Course format

• Live, instructor-led online training
• Hands-on coding with real-world genomic datasets
• Interactive practical exercises throughout
• Strong focus on applied, research-ready workflows

Who is this course for?

• Marine mammal researchers working with genetic or genomic data
• Conservation geneticists and molecular ecologists
• Bioinformaticians and computational biologists
• Researchers interested in applying machine learning to biological questions
• PhD students and quantitative life scientists

Why take this course?

Genomic approaches are increasingly used to address important questions in marine mammal science, including population connectivity, adaptation to changing environments, demographic history, hybridisation, and conservation management. As genomic datasets become larger and more complex, machine learning offers powerful tools for uncovering patterns that may not be apparent using traditional analytical methods.

The techniques covered in this course can be applied to a wide range of marine mammal research questions involving population genomics, conservation genetics, and evolutionary processes. By combining modern machine learning approaches with genomic data, researchers can gain new insights into the factors shaping marine mammal populations and their responses to environmental change.

Learn more & enrol

PR Stats course page for Machine Learning for Evolutionary Genomics (MLEG01)

Questions?

Email: oliver@prstats.org