Application Development with LLMs on Google Cloud
- Course Code GO6592
- Duration 1 day
Course Delivery
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Course Delivery
This course is available in the following formats:
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Company Event
Event at company
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Public Classroom
Traditional Classroom Learning
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Virtual Learning
Learning that is virtual
Request this course in a different delivery format.
Course Overview
TopIn this course, you'll dive into the details of using Large Language Models (LLMs) in your applications. You'll start by exploring the core principles that underpin prompting LLMs. Next, you will focus on Google's latest family of models, Gemini. You'll explore the various Gemini models and their multimodal capabilities. This includes a deep dive into effective prompt design and engineering within the Vertex AI Studio environment. Then, the course moves to application development frameworks and how to implement these concepts into your applications.
- This course does have a deep dive on topics around developing agents using Agent Development Kit and deployment of agents on Google Cloud using solutions such as Agent Engine.
Updated June 2026
Course Schedule
TopTarget Audience
TopCourse Objectives
TopAfter this course participants should be able 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
Course Content
TopIntroduction 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
Vertex AI Studio
- Introduction to Vertex AI Studio
- Designing and testing prompts
- Data governance in Vertex AI Studio
- Lab: Getting Started with the Vertex AI Studio User Interface
Generative AI Fundamentals
- Introduction to grounding
- Integrating the Vertex AI Gemini APIs
- Chat, memory and grounding
- Search principles
- Lab: Getting Started with LangChain + Vertex AI Gemini API
Prompt Engineering
- Review of few-shot prompting
- Chain-of-thought prompting and thinking budgets
- Meta prompting, multi-step, and panel prompts
- RAG and ReAct
- Lab: Advanced Prompt Architectures
Creating Custom Chat Applications with Vertex AI Gemini API
- LangChain for chatbots
- ADK for chatbots
- Chat retrieval
- Lab: Implementing RAG Using LangChain
Course Prerequisites
TopCompletion of "Introduction to Developer Efficiency on Google Cloud" or equivalent knowledge.
Test Certification
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TopFurther Information
TopOfficial course book provided to participants.