Description
AI Engineer MLOps Track: Deploy Gen AI & Agentic AI at Scale is a course published by Udemy Online Academy that teaches you the practical skills needed to build, deploy, and manage modern AI systems in production environments. The AI Engineer MLOps Track: Deploy Gen AI & Agentic AI at Scale is a specialized, industry-focused course designed to help individuals master the practical skills needed to build, deploy, and manage modern AI systems in real-world production environments. The course integrates MLOps principles with the latest advances in Gen AI and Agentic AI, guiding students through the full lifecycle—from model development and automation to scalable deployment, monitoring, and continuous improvement. This course is ideal for AI engineers, data scientists, and developers who want to work at a professional level and in production.
This course explores essential MLOps workflows such as data pipelines, model versioning, CI/CD automation, and container deployment with Docker and Kubernetes, while also covering the integration of LLMs, vector databases, and robust recovery systems. Students gain hands-on experience deploying GenAI models, orchestrating agent-centric AI systems, implementing monitoring and observation tools, optimizing performance for scale, securing production environments, and managing continuous learning pipelines. It also teaches real-world patterns for building AI-powered applications, managing latency and reliability challenges, and leveraging cloud platforms to achieve scalable and automated AI operations. By the end, students understand how to build end-to-end AI systems that are production-ready, efficient, and capable of supporting advanced intelligent agents.
What you will learn in AI Engineer MLOps Track: Deploy Gen AI & Agentic AI at Scale:
- Deploy SaaS LLM applications 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
- Automate deployment to Dev, Test, and Prod with Terraform and continuous deployment via GitHub Actions
- Deliver enterprise-grade AI solutions that are scalable, secure, monitored, explainable, observable, and controllable with Guardrails.
- Build multi-agent systems and agent loops with Amazon Bedrock AgentCore and Stands Agents
- And…
Course specifications
- Publisher : Udemy
- Teacher : Ligency , Ed Donner
- Language: English
- Level : All Levels
- Lectures : 124
- Duration : 18 hours and 40 minutes
Course topics
AI Engineer MLOps Track: Deploy Gen AI & Agentic AI at Scale 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.
Pictures
AI Engineer MLOps Track: Deploy Gen AI & Agentic AI at Scale introduction video
Installation guide
After Extract, watch with your favorite Player.
subtitle: English
Quality: 720p
The 2026/6 version has increased the number of lessons by 2 and the duration increased by 2 minutes compared to 2025/11.
Download link
File password (s): www.downloadly.ir
Size
12.44 GB
