Learn the fundamentals of developing with LLMs!

What you'll do:

• Deeply understand generative AI, describing the key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection, to performance evaluation and deployment
• Describe in detail the transformer architecture that powers LLMs, how they’re trained, and how fine-tuning enables LLMs to be adapted to a variety of specific use cases
• Use empirical scaling laws to optimize the model’s objective function across dataset size, compute budget, and inference requirements
• Apply state-of-the art training, tuning, inference, tools, and deployment methods to maximize the performance of models within the specific constraints of your project
• Discuss the challenges and opportunities that generative AI creates for businesses after hearing stories from industry researchers and practitioners
• Receive a Coursera certificate demonstrating your skills upon completion of the course