Deep Learning A-Z 2026: Mạng Nơ-ron, AI & Giải thưởng ChatGPT
Kirill Eremenko
The Complete Agentic AI Engineering Masterclass (2026)
This course, takes you from the fundamentals of AI models to building and deploying Intelligent AI agents using the latest Generative AI Framework and LLM-powered architectures. Designed for professionals, developers, and innovators, this program blends theory, practice, and hands-on insights.
Over the course, you’ll explore:
Foundations of Generative AI — Dive deep into CNNs, Transformers, Diffusion Models, VAEs, and how modern generative systems produce new content.
Traditional vs Agentic AI Engineering — Understand the shift from static models to reactive agents, and learn why agentic frameworks are the future.
How LLMs Work — Unpack tokenization, embeddings, self-attention, layers, prompts, and the reasoning pipelines behind GPT-style models.
RAG & Fine-Tuning — Learn when to fine-tune versus retrieval, build vector‐based memory systems, and integrate retrieval-augmented generation (RAG) workflows.
Local LLM Deployment — Deploy open-source models like LLaMA, Mistral, and Alpaca on your own infrastructure for security, flexibility, and scale.
Hugging Face & Open-Source Ecosystem — Leverage the Hugging Face Model Hub, datasets, pipelines, and tools to accelerate development.
Agentic AI Projects (Hands-On) — Build independent agents, research assistants, Q&A systems, planning agents, and multi-agent pipelines.
Containerization & Cloud Deployment — Package agents with Docker, Kubernetes, or serverless architectures to deploy them reliably in production settings.
Scaling, Monitoring & Maintenance — Learn how to monitor agent performance, handle errors and fallback mechanisms, manage versioning, and scale gracefully.
By the end, you’ll be able to design, fine-tune, and deploy agentic AI systems confidently using Generative AI frameworks.
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