Master the engineering of generative AI applications with LLMs, focusing on deployment, fine-tuning, and robust system design.
Overview
This Specialization empowers learners to become proficient Generative AI Engineers, focusing on the practical application and deployment of Large Language Models (LLMs). Students will dive deep into prompt engineering techniques, learn how to fine-tune LLMs for specific tasks, and master advanced retrieval-augmented generation (RAG) architectures. The curriculum also covers building robust and scalable LLM-powered applications, including system design, evaluation, and responsible AI practices. Designed for developers, data scientists, and AI engineers, this program equips you with the skills to build, optimize, and deploy cutting-edge generative AI solutions.
Instructor
Sharon Zhou
Adjunct Professor, Stanford University; CEO, Lamini
Sharon Zhou is an Adjunct Professor at Stanford University, specializing in Generative AI, and the CEO of Lamini, a leading enterprise LLM solutions provider.
Learning Outcomes
Master prompt engineering for robust LLM applications
Develop and deploy LLM-powered applications using various APIs
Fine-tune pre-trained LLMs for specific tasks and domains