Module #1 Introduction to Machine Learning in Infectious Disease Research Overview of machine learning, its applications in infectious disease research, and the importance of interdisciplinary collaboration.
Module #2 Infectious Disease Epidemiology and Surveillance Introduction to infectious disease epidemiology, surveillance methods, and data sources.
Module #3 Data Preprocessing for Machine Learning in Infectious Disease Research Handling missing values, data normalization, feature scaling, and data transformation for machine learning applications.
Module #4 Supervised Learning for Disease Prediction Introduction to supervised learning, logistic regression, decision trees, random forests, and support vector machines for disease prediction.
Module #5 Unsupervised Learning for Disease Clustering and Dimensionality Reduction Introduction to unsupervised learning, k-means clustering, hierarchical clustering, and dimensionality reduction techniques (PCA, t-SNE).
Module #6 Deep Learning for Infectious Disease Diagnosis Introduction to deep learning, convolutional neural networks (CNNs), and recurrent neural networks (RNNs) for image and sequence-based data analysis.
Module #7 Natural Language Processing for Infectious Disease Surveillance Introduction to natural language processing (NLP), text preprocessing, and topic modeling for disease surveillance and outbreak detection.
Module #8 Case Study:Predicting Disease Outbreaks using Twitter Data Hands-on exercise using Twitter data to predict disease outbreaks using machine learning algorithms.
Module #9 Machine Learning for Antimicrobial Resistance Prediction Introduction to machine learning for antimicrobial resistance prediction, feature engineering, and model evaluation metrics.
Module #10 Case Study:Predicting Antimicrobial Resistance using Genomic Data Hands-on exercise using genomic data to predict antimicrobial resistance using machine learning algorithms.
Module #11 Machine Learning for Vaccine Development and Optimization Introduction to machine learning for vaccine development, epitope prediction, and vaccine optimization.
Module #12 Case Study:Predicting Vaccine Efficacy using Machine Learning Hands-on exercise using machine learning algorithms to predict vaccine efficacy.
Module #13 Machine Learning for Disease Transmission Modeling Introduction to machine learning for disease transmission modeling, compartmental models, and network analysis.
Module #14 Case Study:Modeling Disease Transmission using Contact Networks Hands-on exercise using contact networks to model disease transmission using machine learning algorithms.
Module #15 Machine Learning for Personalized Medicine in Infectious Diseases Introduction to machine learning for personalized medicine, precision health, and treatment outcome prediction.
Module #16 Ethical Considerations in Machine Learning for Infectious Disease Research Discussion of ethical considerations, bias, and fairness in machine learning for infectious disease research.
Module #17 Collaboration and Communication in Interdisciplinary Research Importance of collaboration and communication between machine learning experts, infectious disease researchers, and clinicians.
Module #18 Real-World Applications of Machine Learning in Infectious Disease Research Case studies and success stories of machine learning applications in infectious disease research, policy, and practice.
Module #19 Future Directions and Emerging Trends in Machine Learning for Infectious Disease Research Discussion of emerging trends, challenges, and opportunities in machine learning for infectious disease research.
Module #20 Hands-on Project Development Students work on a self-directed project applying machine learning to an infectious disease research problem.
Module #21 Project Presentations and Peer Feedback Students present their projects and receive feedback from peers and instructors.
Module #22 Machine Learning for Infectious Disease Surveillance in Low-Resource Settings Challenges and opportunities for machine learning applications in low-resource settings.
Module #23 Machine Learning for Zoonotic Disease Research Introduction to machine learning for zoonotic disease research, animal-human interface analysis, and disease ecology.
Module #24 Machine Learning for Vector-Borne Disease Research Introduction to machine learning for vector-borne disease research, entomological analysis, and vector control optimization.
Module #25 Machine Learning for Infectious Disease Diagnostics Introduction to machine learning for infectious disease diagnostics, diagnostic biomarker discovery, and point-of-care testing.
Module #26 Machine Learning for Infectious Disease Modeling and Simulation Introduction to machine learning for infectious disease modeling, simulation, and scenario analysis.
Module #27 Machine Learning for Infectious Disease Policy and Decision-Making Introduction to machine learning for infectious disease policy, decision-making, and resource allocation optimization.
Module #28 Machine Learning for Infectious Disease Forecasting and Prediction Introduction to machine learning for infectious disease forecasting, prediction, and situational awareness.
Module #29 Machine Learning for Infectious Disease Genomics and Genomic Epidemiology Introduction to machine learning for infectious disease genomics, genomic epidemiology, and phylogenetic analysis.
Module #30 Course Wrap-Up & Conclusion Planning next steps in Machine Learning in Infectious Disease Research career
