English | Size: 1.2 GB
Genre: eLearning
Advance Your AI Expertise: Build Custom LLMs, Master Evaluation (h2oGPT, GenAI)
What you’ll learn
Build custom h2oGPT models using H2O ai tools and techniques.
Employ various evaluation methods to effectively assess model performance.
Understand and utilize the functionalities of LLM EvalGPT.
Analyze and navigate the components of the H2O ai Generative AI Ecosystem.
Building on the foundational knowledge from LLM Level 2, this advanced course, Large Language Models – Level 3 is designed to deepen your expertise in using H2O ai’s cutting-edge Generative AI tools and techniques.
Guided by a team of AI experts including Sanyam Bhutani, Rob Mulla, and Andreea Turcu, the course begins with an in-depth exploration of the H2O ai Generative AI ecosystem, highlighting essential tools like h2oGPT, H2O LLM EvalGPT, and key GenAI components. You will learn how to create your custom h2oGPT models, effectively use various evaluation techniques to assess model performance, and understand the functionalities of LLM EvalGPT. Additionally, you will analyze the elements of the H2O ai GenAI Ecosystem to streamline and enhance your AI workflows.
By the end of this course, you will have the knowledge and confidence to apply these advanced tools and techniques to your business scenarios, making your AI projects more efficient and impactful. This course is ideal for AI and data science professionals, machine learning engineers, researchers, and business professionals looking to advance their skills in generative AI.
Upon successful completion, you will earn the LLM Level 3 Certification, demonstrating your proficiency in using H2O ai tools for the above mentioned variety of generative AI tasks. This certification is a valuable asset for your career in AI and data science.
Who this course is for:
AI and data science professionals seeking to deepen their expertise in generative AI.
Machine learning engineers looking to enhance their skills with H2O ai’s advanced tools.
Researchers and developers interested in creating custom language models and exploring innovative evaluation techniques.
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