Ementorhub

What you'll learn

Learn to prepare and clean datasets for NLP, ensuring high-quality data to improve model outcomes.

Explore LLM DataStudio’s workflows, customize interfaces, and implement efficient data management strategies.

Apply advanced fine-tuning techniques in H2O LLM Studio to optimize language models for specific NLP tasks.

Skills you'll gain

Data Cleansing

Data Transformation

MLOps (Machine Learning Operations)

Verification And Validation

Data Validation

Data Processing

Performance Tuning

Collaborative Software

Large Language Modeling

User Interface (UI)

Feature Engineering

Natural Language Processing

Data Quality

There are 4 modules in this course

Discover the critical role of clean data and effective data preparation techniques essential for NLP model quality. Using LLM DataStudio, navigate supported workflows, customize interfaces, and implement quality control measures. Learn to set up projects and leverage collaboration features to enhance team efficiency. Master QnA dataset creation, ensuring accuracy through validation and quality assurance processes. Perfect fine-tuning with H2O LLM Studio, where you'll tailor models to specific tasks. Explore workflows, employ data augmentation strategies, and select optimal architectures from pre-trained models. Delve deeper into advanced techniques like Quantisation and LoRA for model compression, optimizing your NLP applications for real-world deployment. Earn your LLM Certification Level 2, showcasing your expertise in data preparation, fine-tuning, and model optimization. This certification is ideal for professionals that are aiming to excel in specialized roles within NLP, machine learning, and data engineering. Join Andreea Turcu in this course and elevate your skills in harnessing LLMs for cutting-edge NLP projects, where you’ll dive into practical applications of language models and supercharge your AI career!

Mastering LLM DataStudio

Fine-Tuning Your Large Language Models

Course Completion Quiz