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.
Taught by â‹® Ed Donner, Ligency
$9.99 with coupon (list $159.99 — save $150.00, 94% off)
Coupon Verified: September 10, 2026 · click Claim Coupon to apply the discount code
AI_S···26Course Overview — Key Takeaways
Verified details for this course — last checked September 10, 2026. Rating and student counts are Udemy's own published figures.
- Course Title
- AI Engineer Production Track: Deploy LLMs & Agents at Scale
- Platform
- Udemy (coupon tracked by CoursesWyn)
- Instructor
- Ed Donner, Ligency
- Coupon Last Checked
- September 10, 2026
- Level
- All levels
- Category
- Development
- Topic
- AI Agents & Agentic AI
- Length
- 18 hours 30 minutes of on-demand video
- Language
- English
- Access
- Lifetime access on Udemy
- Certificate
- Certificate of completion
- Top Outcomes
- 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
- Prerequisites
- 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.
- Price
- $9.99 with coupon (list $159.99 — save $150.00, 94% off)
- Coupon
- Hit Claim Coupon — the discount applies at checkout
What You'll Learn
Practical skills and outcomes you'll gain from AI Engineer Production Track: Deploy LLMs & Agents at Scale — taken from the official Udemy syllabus for Development learners.
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
What you need before enrolling in AI Engineer Production Track: Deploy LLMs & Agents at Scale — prerequisites as listed by the instructor on Udemy.
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.
Overview
The full official description of AI Engineer Production Track: Deploy LLMs & Agents at Scale — curriculum, teaching approach, and everything included with this Udemy coupon.
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Frequently Asked Questions
Common queries about this coupon, pricing, and enrollment. Answers reflect our last check on September 10, 2026.
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