LLMOps & GenAI for MLOps

You can learn how to work with LLMs and GenAI

In this course, you will learn how to work with Large Language Models (LLMs) and Generative AI (GenAI) in real-world MLOps systems. These models are powerful, but they also bring new challenges, like cost, monitoring, speed, and safety.

We will explore how MLOps Engineers support the full lifecycle of LLMs – from preparing special data to running the models, tracking outputs, and keeping everything stable and safe. You will also learn how teams handle prompt design, output checks, and build smart search systems to guide the models.

This course is not about training new models. It shows how to run and maintain LLM systems in real products and services. You’ll see how workflows are built, what pipelines are needed, and how to keep systems working well over time.

By the end, you’ll understand how GenAI fits into MLOps and how LLMOps is different from classic ML operations. This course is your starting point into one of the fastest-growing areas in MLOps today.

Course Content

Start learning high demand tech skills today

About Your Instructor

Hi, I’m Alex and I’ve spent over 20 years helping well known startups and enterprises introduce innovations. I also developed and taught Cloud&DevOps part for a Master’s Degree at the University.

In this course, I’ll show you what MLOps looks like in practice – step by step, with real tools and clear guidance.

You don’t need to be an expert. If you want to understand how to start or enforce your career as MLOps Engineer, not just in theory, but in real life, this course is for you. Let’s get started.

All courses are developed by experienced instructors with over 10 years of real-world industry expertise. We focus on delivering practical, up-to-date content – not just collecting enrollments, so that every course gives you real value.

Our courses meet high academic standards, and we’re actively working on certification to ensure they align with recognized best practices.

Each course includes video lectures, hands-on labs with screen recordings, quizzes, reading materials, GitHub repository with real project code, and a capstone project. This structure is designed to help you build practical, in-demand skills and knowledge that employers care about.

However, if you’re not satisfied for any reason, you can request a refund in accordance with our Refund Policy – your satisfaction matters to us.

It’s not just skills. It’s your next chapter.

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