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This hands-on bootcamp is designed to help DevOps Engineers and infrastructure professionals transition into the growing field of MLOps. With AI/ML rapidly becoming an integral part of modern applications, MLOps has emerged as the critical bridge between machine learning models and production systems.
In this course, you will work on a real-world regression use case — predicting house prices — and take it all the way from data processing to production deployment on Kubernetes. You’ll start by setting up your environment using Docker and MLFlow for tracking experiments. You’ll understand the machine learning lifecycle and get hands-on experience with data engineering, feature engineering, and model experimentation using Jupyter notebooks.
Next, you'll package the model with FastAPI and deploy it alongside a Streamlit-based UI. You’ll write GitHub Actions workflows to automate your ML pipeline for CI and use DockerHub to push your model containers.
In the later stages, you'll build a scalable inference infrastructure using Kubernetes, expose services, and connect frontends and backends using service discovery. You’ll explore production-grade model serving with Seldon Core and monitor your deployments with Prometheus and Grafana dashboards.
Finally, you'll explore GitOps-based continuous delivery using ArgoCD to manage and deploy changes to your Kubernetes cluster in a clean and automated way.
By the end of this course, you'll be equipped with the knowledge and hands-on experience to operate and automate machine learning workflows using DevOps practices — making you job-ready for MLOps and AI Platform Engineering roles.
Everything You Need to Know About DevOps to MLOps Bootcamp: Build & Deploy MLSystems End-2-End
This course is a comprehensive and well-structured introduction to DevOps to MLOps Bootcamp: Build & Deploy MLSystems End-2-End. The instructor, Gourav Shah . 140,000+ Students, is a leading expert in the field with a wealth of experience in IT & Software to share.
The course is well-structured and easy to follow, and the instructor does a great job of explaining complex concepts in a clear and concise way.
The course is divided into sections, each of which covers a different aspect related to Other IT & Software. Each module contains a series of video lectures, readings, and hands-on exercises.
The instructor does a great job of explaining each topic in a clear and concise way. He/She also provides plenty of examples and exercises to help students learn the material.
One of the things I liked most about this course is that it is very practical. The instructor focuses on teaching students the skills and knowledge they need to succeed in the real world. He/She also provides students with access to a variety of resources, including templates, checklists, and cheat sheets.
Another thing I liked about this course is that it is offered on Udemy. Udemy is a great platform for taking online courses because it offers a lot of flexibility for students. Students can choose to take courses at their own pace, and they can access the course materials from anywhere with an internet connection.
Udemy also offers a variety of payment options, so students can find a plan that works for them. The course also has a very active community forum where students can ask questions and interact with each other. The instructor is also very responsive to student questions and feedback.
Overall, I highly recommend this course to anyone who is interested in learning DevOps to MLOps Bootcamp: Build & Deploy MLSystems End-2-End. It is a well-organized and informative course that will teach you the skills and knowledge you need to succeed.
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