Machine Learning Basics
Understand features, labels, training, prediction, evaluation, and overfitting.
Simple Model Workflow
Prepare data, train a small model, evaluate it, and save results.
Generative AI and LLM Basics
Use Python to call model APIs, validate structured outputs, and apply safety checks.
Training, Validation, and Test Splits
Separate data correctly so model evaluation reflects future performance.
AI Project Structure
Organize datasets, experiments, models, and reports for reproducible AI work.