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FourthBrain Workshop

Building with LLMs

How to Leverage foundation models

A 3-week LIVE workshop for engineers, developers, and data scientists on building and deploying applications with LLMs. You'll learn to fine-tune LLMs and deploy three applications, including your own domain-specific project. 

  • Date: Coming Soon
  • Time: 4-7pm PT on Tuesdays and Thursdays
  • Cost: $2,000

LLMs and other generative AI capabilities have exploded in recent months. Engineers are no longer building models; you need to learn how to leverage and customize these powerful tools for your own applications. 

In this workshop you will learn to  build and deploy an LLM-powered application using open-source tools and frameworks that are designed specifically to work with LLMs. You'll fine-tune LLMs to improve classic ML algorithm performance, teach LLMs new structure, and build a question-answering tools for your documents. 

As industries adapt to take advantage of AI, businesses around the world are realizing that AI implementation will soon be essential to remain competitive and up-to-date.

Business leaders face the biggest challenge of not knowing how to begin. This workshop, exclusively for executives, directors, and decision-makers, has been designed to help them come up with concrete next steps to create a roadmap for incorporating AI into their businesses.

Key Outcomes

Build and deploy three LLM applications

Fine-tune the structure of state-of-the-art LLMs

Learn to leverage LLMs for common use cases

Workshop Schedule

This workshop includes two live sessions a week on Tuesdays and Thursdays, plus additional practice on your own time. You will also have access to Slack to collaborate with your peers and instructors outside of class time. 

  • Fine-tune LLMs to improve classification performance 
  • Fine-tune the structure of LLMs for your own domain / use case
  • Optimize the way that users will interact with your AI app
  • Work with variety of open-source LLMs
  • Tools: Google Colab, 
Download the Syllabus

This workshop is for you if:

You are an engineer, data scientist, or  developer who wants to add foundation models to your AI workflow

You are eager to build applications with LLMs and understand some of the use cases for these applications

You are fluent in Python and have experience manipulating data, building basic ML models like classifiers, and have deployed an application. 

How to Prepare

Create a Google Colab Account

We suggest you work in Google Colab for fine-tuning, so you should have a paid account. 

Familiarize yourself with Hugging Face

This Introduction to Hugging Face Course will teach you about NLP using libraries from the Hugging Face ecosystem. 

Many employers offer reimbursement for programs like ours. Check out our tips for getting reimbursed.

"67% of companies saw revenue increase due to AI adoption"

- McKinsey Tech Trends Outlook 2022

Register Here

Interested in this program for your team? Reach out!

FAQs

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About FourthBrain

FourthBrain's mission is to bring more people into the growing fields of Machine Learning and Artificial Intelligence through flexible education programs. We equip leaders with the skills to lead organizations towards AI maturity, and support engineers, developers, and data scientists to make an impact in this field.
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About Andrew Ng

Featured Speaker: Dr. Andrew Ng

Dr. Andrew Ng is a globally recognized leader in AI. He is the Founder of DeepLearning.AI and Founder and CEO of Landing AI, and an Advisor to FourthBrain. 

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AI-First Mindset For Leaders

This class was designed to give company decision-makers at various levels, the AI understanding they need to lead from the front. The curriculum has been crafted to fill knowledge gaps for leaders experiencing any of the following:
  • You're struggling to figure out how AI can impact your organization
  • You want to stay ahead of the curve with AI technology, but aren't sure how to start
  • Your organization is experimenting with AI, but has not seen any real business impact from it
  • Your organization has some valuable models, but they are not fully integrated into daily operations