Building Generative AI Applications
A 1-day workshop for engineers, developers, and data scientists on building applications with LLMs and Diffusion Models. With 6 hours of LIVE instruction, you'll build and deploy an end-to-end application
- Next Date: Saturday, June 10
- Time: 9am-3pm PT
- Cost: $500 for Individuals | $1,500 for Teams
LLMs and other generative AI capabilities have exploded in recent months. Learning to leverage these incredibly powerful tools will be a key skill for developers and engineers in the coming months and years. In this workshop you will build, deploy, and share an application using an LLM or Diffusion Model.
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.
Fine-tune Stable Diffusion or BLOOM
Analyze ROI for fine tuning
Deploy using HuggingFace
- ML Models and the open-source MLOps Stack
- Data-Centric Approaches for diffusion models and LLMs
- Leveraging model fine-tuning and prompt engineering to optimize output
This workshop is for you if:
You are eager to dive deeper into building applications with LLMs or diffusion models like ChatGPT, Stable Diffusion, or BLOOM
Register as an Individual
Register as a Team
Price: $1,500 per team
"67% of companies saw revenue increase due to AI adoption"
- McKinsey Tech Trends Outlook 2022
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.
AI-First Mindset For Leaders
- 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