ML for Bioscience
Data → Models → Interpretation
- Fundamentals of machine learning in bioscience research
- Data preprocessing, feature engineering, and scaling techniques
- Supervised learning models for regression and classification
- Evaluation metrics for model assessment
- Model interpretation and biological relevance
- Workflow reproducibility and result presentation
- Immediate access to recorded modules
- Reusable ML workflows for your own research
- Certificate of completion (if included in product package)









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