Introduction
Do you know that you can automate machine learning (ML) deployments and workflow? Yes, you heard right. This can be done through machine learning operations (MLOps), which are a set of rules and practices that simplify and automate ML deployments and workflows. Today, people are creating ai and machine learning solutions that solve real-world problems at a rapid pace. This is only possible when you include MLOps in your entire project. In this article, we bring you the 6 most important free courses on MLOps offered by Google.
Also read: A Comprehensive MLOps Learning Path – 2024 Edition
6 free Google courses on MLOps
As an aspiring data scientist or data enthusiast, you should have a clear understanding of the core concepts of MLOps. So if you are stuck somewhere or don't know where to master these concepts, this article is for you. This curated list will guide you into the world of MLOps with ease as we have categorized the courses from basic to advanced level. Let's start!
1. Machine Learning Operations (MLOps): Introduction
This is the introductory course for beginners, introducing you to the fundamentals of MLOps tools and best practices for deploying, testing, monitoring, and operating production machine learning systems on Google Cloud. MLOps is a discipline focused on deploying, testing, monitoring, and automating ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of implemented models. They work with (or may be) data scientists, who develop models, to enable speed and rigor in deploying the best performing models.
After completing this foundational course, you will earn the badge attached below. Additionally, she can boost her cloud career by displaying the badge on Linkedin and showing the world the skills she has developed.
![Machine Learning Operations (MLOps): Introduction | Free Google Course](https://technicalterrence.com/wp-content/uploads/2024/05/6-Free-MLOps-Courses-Offered-by-Google.png)
2. MLOps: automation pipelines and continuous delivery in machine learning
In this course, you will understand and discuss techniques for implementing and automating continuous integration (CI), continuous delivery (CD), and continuous training (CT) for machine learning (ML) systems. Data science and machine learning are becoming critical capabilities to solve complex real-world problems, transform industries, and deliver value across the board.
![MLOps: Automation Pipelines and Continuous Delivery in Machine Learning](https://technicalterrence.com/wp-content/uploads/2024/05/1715958292_585_6-Free-MLOps-Courses-Offered-by-Google.png)
<h3 class="wp-block-heading" id="h-3-build-and-deploy-machine-learning-solutions-on-vertex-ai“>3. Build and deploy machine learning solutions on Vertex ai
This skill badge course is for professional data scientists and machine learning engineers. The datasets and labs are based on high-impact enterprise machine learning use cases; these include retail customer lifetime value prediction, mobile game churn prediction, visual identification of auto parts churn, and fine-tuning BERT for review sentiment classification.
4. Machine Learning Pipelines on Google Cloud
In this course, you'll learn from Google Cloud's cutting-edge machine learning process developers and trainers. TensorFlow Extended (TFX), Google's production machine learning framework for metadata and machine learning pipelines, will be covered in the first few topics. TFX channel components and orchestration will be covered.
![Machine Learning Pipelines on Google Cloud | Free Course](https://technicalterrence.com/wp-content/uploads/2024/05/1715958292_355_6-Free-MLOps-Courses-Offered-by-Google.png)
<h3 class="wp-block-heading" id="h-5-machine-learning-operations-mlops-with-vertex-ai-manage-features”>5. Machine Learning Operations (MLOps) with Vertex ai: Manage Features
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring, and operating production machine learning systems on Google Cloud. MLOps is a discipline focused on deploying, testing, monitoring, and automating ML systems in production. Students will get hands-on practice using Vertex ai Feature Store streaming ingestion at the SDK layer.
6. Production Machine Learning Systems
This course covers how to implement the different types of production machine learning systems: static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You'll delve into TensorFlow's abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.
![Production Machine Learning Systems | Free Google Course](https://technicalterrence.com/wp-content/uploads/2024/05/1715958292_61_6-Free-MLOps-Courses-Offered-by-Google.png)
Conclusion
There you have it, seven great Google MLOps courses, all available for free! Whether you're diving into machine learning operations or looking to polish your skills, these courses cover everything from the basics to the more complex aspects of MLOps. Not only will you learn about how to implement and optimize machine learning systems, but you'll also get some shiny badges to display on your LinkedIn profile. It is a fantastic opportunity to increase your experience and credibility in this rapidly growing field. Why not start one of these courses today and up your game in the world of machine learning trading? Happy learning!