Large Language Models (LLMs) - Level 2
Build on your foundation in Large Language Models (LLMs) with practical techniques for improving data quality, fine-tuning, and deploying NLP models. This course focuses on hands-on experience with LLM DataStudio and H2O LLM Studio, guiding you through dataset preparation, model customization, and evaluation. Explore advanced topics like quantization and LoRA to optimize model performance for real-world applications. Designed for learners with prior exposure to LLMs, this course helps deepen your understanding and awards you a certification upon completion.
What you'll learn
- Importance of Clean Data for NLP
Understand why data quality matters and how to prepare datasets for reliable NLP models.
- Hands-On with LLM DataStudio
Learn to navigate workflows, customize interfaces, and set up projects in LLM DataStudio.
- Fine-Tuning Techniques
Use H2O LLM Studio to fine-tune models, apply data augmentation, and choose pre-trained architectures.
- QnA Dataset Preparation
Create and validate datasets for question-answering tasks with quality checks and review processes.
- Model Compression Essentials
Apply quantization and LoRA to reduce model size while maintaining performance for deployment.
- Automation with Workflow Builder
Utilize the Workflow Builder in LLM DataStudio to streamline NLP tasks and projects.
Course Playlist on YouTube
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