Instructor: Dr. Sharif Edris (King Abdulaziz University, Jeddah, KSA) | Format: Online | Day: 1
This workshop focuses on applying AI and machine learning in microbiome data analysis. Participants will learn to preprocess, normalize, and visualize microbiome data, and build predictive models linking microbial signatures to health outcomes.
Learning Objectives:
- Understand AI and ML applications in microbiome data analysis
- Learn to preprocess, normalize, and visualize microbiome data
- Build predictive models linking microbial signatures to health outcomes
- Integrate AI-based tools into reproducible analytical workflows
Expected Outcomes:
- Practical skills in applying AI/ML methods to microbiome datasets
- Ability to interpret complex microbial community patterns using visualization and modelling tools
- Understanding of the challenges and future directions of AI in microbiome science
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