استقرار مدل‌های زبانی (LLM) و ایجنت‌های هوشمند در مقیاس عملیاتی

عنوان دوره : Udemy – AI Engineer Production Track: Deploy LLMs & Agents at Scale

سطح : متوسط

زمان کل دوره : 18 ساعت و 40 دقیقه

تعداد فایل ها : 124

سال آموزش : 2026

فایل تمرینی : ندارد

مربی دوره : Ligency Team – Ed Donner

نرم افزار :

زیرنویس انگلیسی : دارد

Udemy – AI Engineer Production Track: Deploy LLMs & Agents at Scale

Deploy AI to AWS, GCP, Azure, Vercel with MLOps, Bedrock, SageMaker, RAG, Agents, MCP: scalable, secure and observable.

What you’ll learn
⚡ Deploy SaaS LLM apps to production on Vercel, AWS, Azure, and GCP, using Clerk
⚡ Design cloud architectures with Lambda, S3, CloudFront, SQS, Route 53, App Runner and API Gateway
⚡ Integrate with Amazon Bedrock and SageMaker, and build with GPT-5, Claude 4, OSS, AWS Nova and HuggingFace
⚡ Rollout to Dev, Test and Prod automatically with Terraform and ship continuously via GitHub Actions
⚡ Deliver enterprise-grade AI solutions that are scalable, secure, monitored, explainable, observable, and controlled with guardrails.
⚡ Create Multi-Agent systems and Agentic Loops with Amazon Bedrock AgentCore and Stands Agents

Requirements
❗ While it’s ideal if you can code in Python and have some experience working with LLMs, this course is designed for a very wide audience, regardless of background. I’ve included a whole folder of self-study labs that cover foundational technical and programming skills. If you’re new to coding, there’s only one requirement: plenty of patience!
❗ The course runs best if you have a small budget for APIs and Cloud Providers of a few dollars. But we monitor expenses at every point, and it’s always a personal choice.

Description

This is the course that more of my students have asked for than any other course — put together.
One student called it

“The missing course in AI.”
This course is for

✨ Entrepreneurs

✨ Enterprise engineers

✨ …and everyone in between.

It’s not just about RAG — although we’ll work with RAG.

It’s not just about Agents — but there will be many Agents.

It’s not just about MCP — but yes, there will be plenty of MCP too.

This course is about

RAG, Agents, MCP, and so much more… deployed to production.
Live.

Enterprise-grade.

Scalable, resilient, secure, monitored — and explained.

You’ll ship real-world, production-grade AI with LLMs and agents across Vercel, AWS, GCP, and Azure, going deepest on AWS.

Across four weeks you’ll take four products to production

Week 1
You’ll launch a Next.js SaaS product on Vercel and AWS,

with AWS App Runner and Clerk for user management and subscriptions.

Week 2
You’ll become an AI platform engineer on AWS,

deploying serverless infrastructure using

✨ Lambda, Bedrock, API Gateway, S3, CloudFront, Route 53

✨ Write Infrastructure as Code with Terraform

✨ Set up CI/CD pipelines with GitHub Actions

— for hands-free deployments and one-click promotions.

Week 3
You’ll gain broad industry skills for GenAI in production

✨ Deploy a Cyber Security Analyst agent with MCP to Azure & GCP

✨ Stand up SageMaker inference

✨ Build data ingest to S3 vectors

✨ Deploy a Researcher Agent using OpenAI OSS models on Bedrock + MCP

Week 4
You’ll go fully agentic in production

✨ Architect multi-agent systems with

✨ Aurora Serverless, Lambda, SQS

✨ JWT-authenticated CloudFront frontends

✨ LangFuse observability

✨ Overview of AWS Agent Core