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Unlock the transformative power of Generative AI with Python! This comprehensive course equips you with the essential knowledge and practical Python skills to master the core technologies driving this revolution, enabling you to build intelligent applications that understand, generate, and interact with language remarkably.You'll delve into the fundamentals of Large Language Models (LLMs) and the crucial role of Vector Databases for efficient information retrieval. Discover the power of Retrieval-Augmented Generation (RAG), which allows your AI to answer complex questions using your own data, making it smarter and more contextually aware.Furthermore, you'll explore the exciting domain of Agentic Systems, learning how to design and build autonomous AI agents capable of performing tasks and making decisions.In my course I will teach you:Large-Language ModelsClassical NLP vs. LLM Narrow AI Achievements Model Performance and Achievements Model Training Process Model Improvement Options Model Providers Model Benchmarking Interaction with LLMsMessage TypesLLM ParametersLocal Use of ModelsLarge Multimodal ModelsTokenizationReasoning ModelsSmall Language ModelsJailBreakingWorking with ChainsParallel Chains, Router Chains, ...Vector DatabasesData Ingestion PipelineData source and data loadingdata chunkingembeddingsdata storagedata queryingRetrieval-Augmented GenerationBaseline RAGContext EnrichmentCorrective RAGHybrid RAGQuery ExpansionSpeculative RAGAgentic RAGAgentic SystemscrewAIGoogle ADKOpenAI Agents SDKAG2LangGraph (coming soon)Agent InteractionsMCPACPA2A
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