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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 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 workflows with Google Gemini CLI and Docker MCP integration. Learn context engineering, automated evaluations, CI/CD pipelines, and production deployment strategies.
Master AI agent development using Google's Agent Development Kit through hands-on workshops covering single agents, multi-agent orchestration, workflow design, and memory implementation.
Explore how AI agents can safely spend money through NetMind.AI's Agent Payments Protocol, covering secure authorization, digital contracts, and real-world business applications.
Master building AI agents with Python, LangChain, and Oracle Database 23ai through hands-on exercises covering data reasoning, tool integration, and conversational context.
Explore enterprise AI scaling with hybrid search, tensor databases, and multi-modal retrieval. Overcome RAG chatbot challenges through practical demos in medical and e-commerce applications.
Explore how knowledge graphs enhance GenAI trustworthiness through Graph RAG, reducing hallucinations and adding context to AI responses using detective story examples.
Explore cutting-edge applications of LLMs with GraphRAG and intelligent agents, covering implementation strategies, knowledge graph integration, and practical use cases for AI systems.
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.
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