Application Development with LLMs on Google Cloud
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.
- Duration: 1 day
- Languages: English, German
- Level: Intermediate
- Group size: Up to 16
What you'll learn
- 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.
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
Generative AI Fundamentals
- Introduction to grounding
- Integrating the Vertex AI Gemini APIs
- Chat, memory and grounding
- Search principles
Prompt Engineering
- Review of few-shot prompting
- Chain-of-thought prompting and thinking budgets
- Meta prompting, multi-step, and panel prompts
- RAG and ReAct
Creating Custom Chat Applications with Vertex AI Gemini API
- LangChain for chatbots
- ADK for chatbots
- Chat retrieval
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Not sure which course fits?
Book a 30-minute call. We'll look at where your team is, what they need to be able to do, and put together either a specific course date or a tailored learning plan.