This course teaches participants core prompting principles and focuses on Google's Gemini models (Flash-lite, Flash, Pro) and their multimodal capabilities. The course covers accessing these models through the Google AI APIs and Vertex AI, including prompt design in Vertex AI Studio. A large part of the training is dedicated to application frameworks like LangChain and Agent Development Kit, covering concepts such as RAG (Retrieval Augmented Generation) and agents. Application Development with LLMs on Google Cloud v.2.0 Benefits This course will empower you to: Explore the different options available for using generative AI on Google Cloud. Use Vertex AI Studio to test prompts for large language models. Develop LLM-powered applications using generative AI Apply advanced prompt engineering techniques to improve the output from LLMs Build a multi-turn chat application using the Gemini API and LangChain. Prerequisites Completion of "Introduction to Developer Efficiency on Google Cloud" or equivalent knowledge. Who Should Attend: Application developers and others who wish to leverage Large Language Models (LLMs) in applications. LLM App Dev on Google Cloud Course Training Outline Learning Objectives Module 1 Introduction to Generative AI on Google Cloud What is generative AI Vertex AI on Google Cloud Generative AI options on Google Cloud Introduction to course use case Module 2 Vertex AI Studio Introduction to Vertex AI Studio Designing and testing prompts Data governance in Vertex AI Studio Module 3 Generative AI Fundamentals Introduction to grounding Integrating the Vertex AI Gemini APIs Chat, memory and grounding Search principles Module 4 Prompt Engineering Review of few-shot prompting Chain-of-thought prompting and thinking budgets Meta prompting, multi-step, and panel prompts RAG and ReAct Module 5 Creating Custom Chat Applications with Vertex AI Gemini API LangChain for chatbots ADK for chatbots Chat Retrieval
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