Description
LLM Engineering: Build Production-Ready AI Systems is a course on designing, developing, and deploying large language model (LLM) applications published by Udemy Online Academy. This is a comprehensive, hands-on course that teaches you how to design, develop, and deploy large language model (LLM) applications that are reliable, scalable, and ready for real-world use. You will learn the core principles of LLM architectures, agile engineering, and context management, then apply these fundamentals to build systems that integrate with APIs, handle diverse user inputs, manage state and memory, and provide useful outputs in use cases such as chatbots, summarization tools, and automation assistants. The course also covers software engineering best practices for version control, testing, monitoring, and performance optimization, as well as strategies for deploying AI safely and responsibly.
Large Language Models (LLMs) are the AI systems behind tools like ChatGPT – models trained on massive amounts of text to understand instructions, generate content, reason based on the text, and invoke tools to perform tasks. But building real, reliable, production-level LLM applications requires much more than just “declaration.” In this course, you’ll learn the full LLM engineering skill set, from foundation and declaration to RAG, agents, observability, security, testing, optimization, and production deployment.
What you will learn in LLM Engineering: Build Production-Ready AI Systems:
- Understand how large language models work, including tokens, context windows, and inference
- Design effective instructions and rapid strategies for reliable and controllable LLM behavior
- Build modular LLM pipelines using core LangChain components
- Implement Retrieval Augmentative Generation (RAG) systems with embeddings and vector databases
- Design agent-based and stateful workflows using LangGraph
- Debug, trace, and evaluate LLM applications using LangSmith
- Build multimodal LLM applications combining text, image, audio, and tools
- Engineer production-ready LLM systems with scalability, reliability, and cost control
- Apply security, safety, and governance best practices to LLM applications
- Test, benchmark, and optimize LLM pipelines for quality, latency, and cost
- Design and deliver a complete LLM system from start to finish as a final project
- And…
Course specifications
Publisher: Udemy
Instructors: Uplatz Training
Language: English
Level: Introductory to Advanced
Number of Lessons: 39
Duration: 17 hours and 34 minutes
Course topics
LLM Engineering: Build Production-Ready AI Systems Prerequisites
Enthusiasm and determination to make your mark on the world!
Pictures
LLM Engineering: Build Production-Ready AI Systems introduction video
Installation guide
After Extract, watch with your favorite Player.
English subtitle
Quality: 1080p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
11.1 GB
