Fine-Tuning and Personlizing LLMs for Engineers

In Collaboration With
UnslothUnsloth
GoogleGoogle
Hugging FaceHugging Face

Course Outline

Fine-Tuning LLMs with Synthetic Data for Personalization and Automation

Learning Outcomes

  • Learn the fundamentals of fine-tuning large language models (LLMs).
  • Create and synthesize data for personalized AI training.
  • Explore the use of Hugging Face and Google Gemma for model fine-tuning.

Who Is This Course For?

  • Engineers looking to understand how to develop their own modelsEngineers looking to work with small open-source language models

Pre-requisites

  • Working experience with open-source language modelsIntermediate python experienceExperience with model deployment or cloud computing infrastructure
LevelAdvanced
Your Instructor
I
Instructor
Duration4 hours
Showcasing
UnslothUnsloth
Why Enroll?
In this hands-on course, engineers will learn the techniques and strategies needed to fine-tune large language models (LLMs) using synthetic data, optimizing them for personalized tasks like automating emails and SMS responses. Leveraging frameworks from Hugging Face and Google's Gemma, this course demonstrates how to clone your personal communication style into AI models. Engineers will walk away with practical knowledge of building highly customized AI tools, turning everyday tasks like email responses into scalable, automated workflows while retaining human-like nuance.
Coming Soon