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 access

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Andreea Turcu, Head of Global Training

Andreea is a data scientist with over 7 years of experience in demystifying AI and Data Science concepts for anyone keen on working in this exciting field using cutting-edge technology. Having obtained a Master’s Degree in Quantitative Economics and Econometrics from Lumière Lyon 2 University, she enjoys integrating machine learning principles with real-world applications. Andreea’s passion lies in developing engaging training programs and ensuring an optimal customer education journey. As she frequently likes to remark, “AI is essentially Economics turbocharged by data, with a sprinkle of innovation.”

You can view her LinkedIn profile HERE.