This course is part of MLOps | Machine Learning Operations Specialization
We are actively working on LLMOps & GenAI for MLOps Course and it will be AVAILABLE SOON.
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What you’ll learn
✓ Understand how Large Language Models (LLMs) work and how to use them in real MLOps tasks.
✓ Learn to build GenAI tools using RAG, prompts, and vector databases like FAISS or Pinecone.
✓ Use Hugging Face, LangChain, and open-source tools to manage LLM pipelines in production.
✓ Track, monitor, and control LLMs with MLflow, logging tools, and simple evaluation methods.
There are 13 modules in this course
- Introduction
- LLM Architectures & Foundations
- Data Management for LLMs
- Infrastructure for LLMOps
- Training & Fine-Tuning LLMs
- Deployment Strategies for LLMs
- RAG (Retrieval-Augmented Generation)
- Observability and Monitoring for LLMs
- Compliance, Safety & Ethics
- Cost & FinOps Considerations
- Tooling & Frameworks
- Use Cases
- Capstone Project
About this course
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 and useful, but they also bring new challenges when it comes to running them in production – things like cost, monitoring, speed, and safety.
We will explore how MLOps Engineers support the full lifecycle of LLMs – from preparing special types of data to running the models, tracking their outputs, and making sure everything stays fast, safe, and under control. You will also learn how teams manage new tasks like prompt design, output evaluation, and building smart search systems that help LLMs use the right information.
This course is not about building new models from scratch. Instead, it shows how to operate and maintain LLM-based systems inside real products and services. You will see how workflows are designed, what kind of pipelines are needed, and how to keep things stable and cost-effective over time.
By the end of the course, you will understand how GenAI fits into the MLOps world. You will be ready to support teams working with modern AI systems, and you will know what makes LLMOps different from working with smaller, classic ML models. This course is your entry point into one of the fastest-growing areas of MLOps today.
Start learning high demand tech skills today
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.
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