Machine Learning
Application Development with LLMs on Google Cloud
Discover how large language models (LLMs) can revolutionize your application development! In this one-day course, you’ll learn how to leverage LLMs to create smarter, more intuitive applications using the latest in AI-driven technologies
1 Days
Target Audience
Who should attend?
Anyone interested in learning how to leverage generative AI on Google Cloud and exploring how LLMs can transform application development
What you'll learn
Leverage generative AI on Google Cloud to enhance applications.Use Vertex AI Studio for testing and optimizing LLM prompts.Build LLM-powered apps with LangChain and optimize output through prompt engineering. Develop multi-turn chat applications with PaLM API and LangChain.
Prerequisites for Success
Prerequisites for Success
omplete the Introduction to Developer Efficiency on Google Cloud course first to build a strong foundation for this session
COURSE AGENDA
Introduction to Generative AI on Google Cloud
- Vertex AI on Google Cloud: Explore Vertex AI and its integration with Google Cloud for machine learning applications.
- Generative AI Options: Learn about the different generative AI options available on Google Cloud, enabling advanced AI-driven features.
- Introduction to Course Use Case: Get an overview of the course use case, focusing on generative AI applications.
Vertex AI Studio
- Introduction to Vertex AI Studio: Understand the capabilities of Vertex AI Studio and how it streamlines working with generative models.
- Available Models and Use Cases: Explore the various models available within Vertex AI Studio and their use cases.
- Designing and Testing Prompts: Learn how to design and test prompts in the Google Cloud console to interact with large language models (LLMs).
- Data Governance in Vertex AI Studio: Understand the data governance practices in Vertex AI Studio to ensure secure and ethical use of data.
LangChain Fundamentals
- Introduction to LangChain: Discover LangChain and its role in integrating large language models (LLMs) with various applications.
- LangChain Concepts and Components: Learn the core concepts and components of LangChain for building AI-driven applications.
- Integrating the Vertex AI PaLM APIs: Understand how to integrate Vertex AI PaLM APIs with LangChain for advanced AI workflows.
- Question / Answering Chain Using PaLM API: Build a question-answering chain using the PaLM API to enable interactive AI applications.
Prompt Engineering
- Review of Few-Shot Prompting: Explore the concept of few-shot prompting and how it can optimize generative AI models.
- Chain-of-Thought Prompting: Learn how chain-of-thought prompting improves the reasoning capabilities of AI models.
- Retrieval Augmented Generation (RAG): Discover Retrieval Augmented Generation (RAG) and how it enhances AI’s ability to answer questions
Creating Custom Chat Applications with Vertex AI PaLM API
- LangChain for Chatbots: Use LangChain to create powerful chatbots with Vertex AI models.
- Memory for Multi-Turn Chat: Learn how to implement memory for multi-turn conversations in chat applications, making them more contextual and dynamic.
- Chat Retrieval: Integrate chat retrieval to provide more accurate responses and better user interactions in real-time.