The Only Free Course You Need To Become a MLOps Engineer

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The world of machine learning (ML) is rapidly evolving, and it has become crucial to operationalize ML models. This is where MLOps comes in to transition ML models from experimentation to production seamlessly. The demand for skilled MLOps engineers is surging, and companies are willing to pay upward of 300K USD.

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 equip you with the practical knowledge and skills needed 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 productionizing machine learning services — from training and experimenting to model deployment and monitoring. The course is tailored for data scientists, ML engineers, software engineers, and data engineers who are keen on learning about putting ML into production.

 

Pre-requisites

 

To get the most out of this course, participants should have a basic understanding of Python and Docker and be comfortable with the command line tools. This is an advanced course requiring 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

 

• Self-paced Learning: All course materials are freely available for you to progress at your own pace.
• Community Support: Join DataTalks.Club’s Slack and the #course-mlops-zoomcamp channel for peer and instructor support.
• Hands-on Experience: The course emphasizes practical knowledge with a project that covers all the learned concepts.
• Earn Certificate: You must complete a final project to get a certificate.
• It is Free: All resources are available for free, without any restrictions. You can access the full experience without any paywalls.
• Expert Instructors: Learn from experienced instructors including Cristian Martinez, Jeff Hale, Alexey Grigorev, Emeli Dral, and Sejal Vaidya.

 

 

 

Each module includes a combination of video lectures, practical exercises, homework assignments, and further reading materials to deepen understanding and application of the concepts. This course aims to provide participants with a solid foundation in MLOps, preparing you 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: Experiment tracking and model management with MLflow.
• Module 3: Orchestration and ML Pipelines using Prefect 2.0.
• Module 4: Model Deployment including web service, streaming, and batch processes.
• Module 5: Model Monitoring with Prometheus, Evidently, and Grafana.
• Module 6: Best Practices in testing, Python linting, CI/CD, and more.

 

 

Throughout the duration of this course, we have gained a comprehensive understanding of machine learning concepts, techniques, and best practices. Now, the ultimate objective of this project is to apply all the knowledge and skills we have acquired 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 tracking the model metrics. To streamline the process, we will create the model pipeline and deploy the model in batch, web service, or streaming. We will monitor the model in production and improve our project by following best practices.

 

 

• Sign Up: Register for the course here: https://airtable.com/shrCb8y6eTbPKwSTL
• Slack Community: Register in DataTalks.Club’s Slack and join the #course-mlops-zoomcamp channel for support and discussion.
• Course Videos: Start the course at your own pace by watching the videos provided in the playlist.
• Stay Updated: To stay updated with the upcoming events, please subscribe to the public Google Calendar.

 

 

The MLOps Zoomcamp by DataTalks.Club is a course collection containing exercises, video tutorials, homework, 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 switch careers, upskill, or solidify your understanding of MLOps, this course stands as the only free resource you’ll need to achieve your goals. So why wait? Sign up today and venture on your MLOps journey.
 
 

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in Technology Management and a bachelor’s degree in Telecommunication Engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.