Vertex AI Multimodal LLMs Training introduces participants to building, deploying, and managing large language models that work across text, images, and other modalities using Google Vertex AI. The course focuses on multimodal AI concepts, foundation models, prompt design, and enterprise use cases powered by Google Cloud’s generative AI ecosystem.

• Understand the fundamentals of multimodal LLMs using Vertex AI
• Learn how to process and generate text, image, audio, and video-based AI outputs
• Build and integrate multimodal AI applications using Vertex AI services and APIs
• Apply prompt engineering techniques for multimodal AI workflows and interactions
• Explore Generative AI model deployment, orchestration, and scalability concepts
• Understand responsible AI, security, and governance practices for multimodal AI systems

• AI engineers and machine learning practitioners
• Cloud developers and architects
• Data scientists working with generative AI
• Enterprise AI and innovation teams
• Technical leads adopting multimodal AI

• Basic understanding of machine learning or generative AI concepts
• Familiarity with Google Cloud fundamentals
• Prior exposure to LLMs or Vertex AI is helpful but not mandatory

• Understanding multimodal LLM concepts and architectures
• Using Vertex AI foundation and multimodal models
• Designing prompts for text, image, and multimodal inputs
• Deploying and managing multimodal LLM applications
• Applying responsible AI principles to generative models

By the end of this training, participants will be able to design, deploy, and manage multimodal LLM applications using Vertex AI while following best practices for scalability, security, and responsible AI.

Introduction to Multimodal LLMs on Vertex AI
• Overview of multimodal large language models
• Vertex AI foundation and generative models
• Multimodal AI use cases in enterprises

Working with Text and Image Models
• Text generation and understanding using LLMs
• Image understanding and captioning
• Combining text and visual inputs

Prompt Engineering for Multimodal AI
• Prompt patterns for multimodal tasks
• Context management and grounding
• Improving output accuracy and relevance

Building Multimodal Applications
• Designing end-to-end multimodal workflows
• Integrating multimodal LLMs with applications
• API usage and orchestration

Deployment, Scaling, and Monitoring
• Deploying multimodal models on Vertex AI
• Performance optimization and cost control
• Monitoring quality and usage

Responsible AI and Governance
• Safety, bias, and ethical considerations
• Explainability and transparency
• Enterprise compliance and governance

• Fundamentals of multimodal LLMs and Vertex AI capabilities
• Multimodal data processing and AI workflow concepts
• Prompt engineering for multimodal AI applications
• AI model integration and deployment techniques
• Security, governance, and responsible AI considerations
• Practical hands-on multimodal AI implementation exercises

• Multimodal prompt design exercises
• Application development tasks
• Final practical assessment

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants will receive an AcadNXT Certification in Vertex AI Multimodal LLMs Training, validating their expertise in multimodal generative AI using Google Cloud.