1. Fundamentals of Chemical Sensors and Biosensors 2. Fundamentals of Machine Learning (ML) and Artificial Intelligence (AI) 3. Use of ML/AI in Chemical Sensors and Biosensors 4. ML-Assisted E-nose and Gas Sensors 5. ML-Assisted FTIR and Raman Spectroscopic Sensing in Agricultural and Food Systems 6. ML-Assisted Surface-Enhanced Raman Spectroscopic Characterization of Biological Systems 7. AI-Assisted Microscopic Imaging Analysis for High Throughput Phenotyping 8. ML-Assisted Lens-Free Imaging 9. ML-Assisted Multispectral and Hyperspectral Imaging 10. AI/ML-Assisted NIR/Optical Biosensing for Plant Phenotyping 11. ML-Assisted Receptor-Free Biosensing 12. ML-Assisted Flow Velocity Analysis in Paper Microfluidics 13. AI/ML Tools for Single Molecule Data Analysis in Biomedicine 14. ML-Assisted Characterization of In Situ Protein Dynamics at Solid-Liquid Interfaces 15. AI-Assisted Microbial Population Dynamics Modeling 16. AI-Assisted All-in-One Sensor System