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The world of machine learning (ML) is evolving rapidly and it has become crucial to get ML models up and running. This is where MLOps comes in to transition ML models from experimentation to production seamlessly. The demand for engineers trained in MLOps is increasing and companies are willing to pay more than $300,000.
To meet this growing demand, DataTalks.Club has launched an exceptional opportunity for both aspiring and seasoned professionals – the MLOps Zoomcamp course. This comprehensive course is designed to give you the practical knowledge and skills necessary to excel in the field of MLOps. And the best part? It's completely free!
Objective and target audience
mlops course from DataTalks.Club teaches the practical aspects of producing machine learning services, from training and experimentation to model deployment and monitoring. The course is designed for data scientists, ML engineers, software engineers, and data engineers who are interested in learning how to put ML into production.
Previous requirements
To get the most out of this course, participants should have a basic understanding of Python and Docker and be comfortable with command-line tools. This is an advanced course that requires one year of experience in both machine learning and programming. If you are new to machine learning or data science, try checking out 5 free courses to master data science.
Key Features
- Learning at your own pace: All course materials are freely available so you can progress at your own pace.
- Community Support: Join the DataTalks.Club Slack and #course-mlops-zoomcamp channel for peer and instructor support.
- Practical experience: The course emphasizes practical knowledge with a project that covers all the concepts learned.
- Get certificate: You must complete a capstone project to earn a certificate.
- It's free: All resources are available for free, without restrictions. You can access the full experience without any paywall.
- Expert instructors: Learn from experienced instructors like Cristian Martinez, Jeff Hale, Alexey Grigorev, Emeli Dral, and Sejal Vaidya.
Each module includes a combination of video lectures, practical exercises, assignments and additional reading materials to deepen the understanding and application of the concepts. This course aims to provide participants with a solid foundation in MLOps, preparing them to handle real-world challenges in deploying and managing machine learning models efficiently.
- Module 1: Introduction to MLOps, MLOps maturity model, and course overview.
- Module 2: Tracking experiments and managing models with MLflow.
- Module 3: Orchestration and machine learning pipelines with Prefect 2.0.
- Module 4: Implementation of models that include web services, streaming and batch processes.
- Module 5: Model monitoring with Prometheus, Evident and Grafana.
- Module 6: Best practices in testing, Python linting, CI/CD, and more.
Throughout this course, we have gained a comprehensive understanding of machine learning concepts, techniques, and best practices. Now, the ultimate goal of this project is to apply all the knowledge and skills we have gained so far and work towards developing a complete end-to-end machine learning solution.
We will first select the dataset and then train our model while keeping track of the model metrics. To speed up the process, we will create the model pipeline and deploy it in batch, web service, or streaming. We will monitor the model in production and improve our project following best practices.
- Register: Register for the course here: https://airtable.com/shrCb8y6eTbPKwSTL
- Loose community: Sign up to DataTalks.Club Slack and join the #course-mlops-zoomcamp channel for support and discussions.
- Course videos: Start the course at your own pace by watching the videos provided in the playlist.
- Stay updated: To stay up to date with upcoming events, subscribe to the public google calendar.
DataTalks.Club's MLOps Zoomcamp is a collection of courses containing exercises, video tutorials, assignments, and practical examples. You will learn how to build, deploy, and monitor machine learning models alongside professionals in the field of data and machine learning.
Whether you're looking to change careers, improve your skills, or solidify your understanding of MLOps, this course is the only free resource you'll need to achieve your goals. So why wait? Sign up today and adventure on your MLOps journey.
Abid Ali Awan (@1abidaliawan) is a certified professional data scientist who loves building machine learning models. Currently, he focuses on content creation and writing technical blogs on data science and machine learning technologies. Abid has a Master's degree in technology Management and a Bachelor's degree in Telecommunications Engineering. His vision is to build an artificial intelligence product using a graph neural network for students struggling with mental illness.
