This course builds on the Level 1 overview with a deeper look at Large Language Models and practical GenAI workflows.
Learn how to work with RAG techniques, fine-tune models, prepare datasets, and evaluate performance using tools like Enterprise h2oGPTe, LLM DataStudio, EvalGPT, and the GenAI AppStore.
Led by Kaggle Grandmaster Sanyam Bhutani, the course includes Python labs, research-based materials, and guided practice using H2O.ai tools across the GenAI ecosystem.
What you'll learn
- Large Language Model Fundamentals
Build understanding of how LLMs work and their role in enterprise AI applications.
- RAG Implementation Techniques
Apply practical retrieval-augmented generation methods using Enterprise H2OGPTe.
- Fine-Tuning with LLM DataStudio
Configure and train language models using H2O's specialized fine-tuning platform.
- Dataset Preparation Best Practices
Structure and prepare data effectively for training and evaluating language models.
- Model Evaluation Methodologies
Use H2O.ai EvalGPT and assessment frameworks to measure model performance and quality.
- H2O GenAI Platform Navigation
Work with GenAI AppStore, H2O.ai Wave, and integrated ecosystem tools for end-to-end workflows.
Course access

