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Application Development with LLMs on Google Cloud

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 !

In 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.

Updated June 2026

GK# 899029 Vendor# GCP-APPDEV-LLMS
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Who Should Attend?

This course is intended for application’s developers interested in LLMs and AI Agents

What You'll Learn

Upon successful completion of this training, 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 Outline

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

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
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Prerequisites

Participants should have notions about development efficiency as acquired in” Introduction to Developer Efficiency with Gemini on Google Cloud” or have equivalent professional knowledge.

  • Introduction to Developer Efficiency with Gemini on Google Cloud