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Dive into a practical journey of building a sales agent application using Google's Gemini models and Retrieval-Augmented Generation (RAG), covering implementation challenges, prompt engineering, and real business impact.
Discover how to build AI agents that transform unstructured data into searchable insights, from basic implementations to advanced multi-agent systems.
Discover how to build next-generation AI applications using Google's Gemini model family and Vertex AI platform, exploring multimodal capabilities, reasoning, and enterprise-ready deployment options.
Discover a pragmatic, battle-tested approach to AI design and delivery, focusing on how design, engineering, and operations must work together to prevent common pitfalls in AI initiatives.
Discover how to create predictable agent workflows that pause for human input, from intro concepts to building a scheduling agent with Portia AI.
Master AI agent development fundamentals using Google's ADK through hands-on coding sessions, tool integrations, and cloud deployment strategies with expert Google instructors.
Dive into FastMCP and tool integration for AI agents with Google experts through hands-on coding, theory, and Q&A in this comprehensive workshop series.
Explore OpenAI's ecosystem through hands-on experimentation with APIs, discover how to build AI assistants, and understand practical applications and limitations of these powerful tools.
Master the art of crafting effective AI prompts while exploring advanced techniques and building practical prototypes to enhance your prompt engineering capabilities.
Dive into local Llama 2 implementation using Ollama, exploring model size and performance trade-offs for efficient AI deployment.
Explore the groundbreaking capabilities of Google Gemini's multi-modal AI system, understanding how it processes text, images, and audio for advanced applications.
Discover essential design patterns and core components for building LLM applications with Vertex AI, from context window optimization to RAG pipelines and agent-based tools.
Dive into advanced RAG optimization techniques, exploring hybrid vector search and embedding strategies to enhance search quality and user experience in GenAI systems.
Discover how to enhance Gemini models' reliability through grounding techniques, connecting AI responses to real-world data using Vertex AI and Google Search integration for improved accuracy.
Master GitHub Copilot's AI-powered features for faster coding, from crafting effective prompts to generating tests, handling SQL, and automating various development tasks across multiple languages.
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