Description
Context Engineering Masterclass: LLMs, RAG & Agents is a course on designing and managing the context that modern AI systems use to produce accurate, relevant, and reliable results, published by Udemy Online Academy. Designed for AI engineers, developers, data scientists, and professionals building productive AI applications, this course explores how to structure information, notifications, retrieved knowledge, tool outputs, memory, and agent state for effective LLM workflows. Learners will work with context windows, notification construction, retrieval augmented generation (RAG), embeddings, retrieval strategies, memory, tool invocation, and agent workflows while learning how to reduce irrelevant information and improve AI performance.
If you’ve ever struggled with LLMs falling into disarray, ignoring instructions, or losing information in long conversations, the problem is usually not the model—it’s the context you’re giving it. This course teaches you how to systematically design, assemble, and optimize the framework for large-scale language models, RAG systems, and AI agents so that your applications perform consistently in production. Whether you’re building chatbots, RAG-based search, or automated AI agents, you’ll come away with a practical framework that you can immediately apply to your projects.
What you will learn in Context Engineering Masterclass: LLMs, RAG & Agents:
- Build production-grade RAG systems using chunking, hybrid search, reranking, and compression
- Design memory systems for AI apps, including short-term, long-term, and agent memory
- Evaluate and improve RAG quality with metrics, context audits, and observability
- Engineer context for AI agents using templates, tool outputs, and multi-step state management
- Apply production and enterprise patterns for scalable, secure, cost-effective LLM applications
- Implement prompt caching strategies that reduce API costs by up to 90%
- Create team context standards, versioning workflows, and reusable context libraries
- and …
Course specifications
Publisher: Udemy
Instructors: Paulo Dichone | Software Engineer, AWS Cloud Practitioner & Instructor
Language: English
Level: Introductory to Advanced
Number of Lessons: 52
Duration: 10h 13m
Course topics
Context Engineering Masterclass: LLMs, RAG & Agents Prerequisites
Basic familiarity with LLMs or generative AI tools such as ChatGPT, Claude, or an LLM API is recommended
Some programming experience (Python or JavaScript) helps with the practical implementation examples
No prior RAG or vector database experience is required; all concepts are explained from the ground up
Pictures
Context Engineering Masterclass: LLMs, RAG & Agents introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
9.7 GB