5 Google MLOps Courses to Improve Your ML Workflow

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MLOps is essential to the success of any machine learning system in production. Therefore, it is not surprising that organizations are looking for engineers trained in MLOps. But what does an MLOps engineer do?

The role of the MLOps engineer is fluid and varies from organization to organization. However, it is compelling and easy to think that an MLOps engineer is more well-rounded than a data scientist. Which means his work goes beyond building machine learning models, with roles in model building, deployment, monitoring, and more.

This article is a compilation of Google MLOps courses. Which will help you learn the fundamentals of production machine learning systems with a focus on Google's Vertex ai platform.

Let us begin!

1. Production Machine Learning Systems

To understand and appreciate MLOps, it is important to first understand how machine learning systems work in production. He Production Machine Learning Systems The course will help you learn about deploying machine learning systems in production by focusing on:

• Static, dynamic and continuous training.
• Static and dynamic inference.
• Batch and online processing

Here are some of the key modules of this course:

• Production Machine Learning System Design
• Designing adaptive machine learning systems
• Design of high-performance ML systems
• Building hybrid machine learning systems

Link: Production Machine Learning Systems

2. Machine Learning Operations (MLOps): Introduction

He Machine Learning Operations (MLOps): Introduction The course is an introduction to machine learning operations. Then you'll learn how to deploy, test, monitor, and evaluate machine learning systems in production.

You'll be introduced to tools and best practices for MLOps and learn about Google's Vertex ai platform. The modules of this course are the following:

• Employ machine learning operations
• Vertex ai and MLOps on Vertex ai

Link: Machine Learning Operations (MLOps): Introduction

3. Machine Learning Operations (MLOps) with Vertex ai: Manage Features

He Machine Learning Operations (MLOps) with Vertex ai: Manage Features The course will help you expand your knowledge on how to perform MLOps on the Google Cloud platform with a focus on the Vertex ai feature store.

This way, you will become familiar with deploying, monitoring, and operating machine learning systems on Google Cloud. Introduces you to the Vertex ai feature store and its key capabilities.

Link: Machine Learning Operations (MLOps) with Vertex ai: Manage Features

4. Machine Learning Pipelines on Google Cloud

This course Machine Learning Pipelines in Google Cloud is an in-depth course that focuses on building and orchestrating machine learning pipelines on Google Cloud Platform. This course has several modules covering the following key topics:

• Created and orchestrated machine learning pipelines using TensorFlow Extend (TFX), Google's production machine learning platform.
• CI/CD for machine learning
• Automating machine learning pipelines
• Using Cloud Composer to organize continuous training processes

Link: Machine Learning Pipelines in Google Cloud

5. Build and deploy machine learning solutions on Vertex ai

In it Build and deploy machine learning solutions on Vertex ai Of course, you will work on real-world use cases to train and deploy machine learning solutions.

In this course, you will be able to dive deeper into the following enterprise ML use cases:

• Retail Customer Lifetime Value Prediction
• Mobile game abandonment prediction
• Visual identification of defects in automobile parts
• Tuning BERT for Review Sentiment Classification

Along the way, you'll also learn how to leverage AutoML.

Link: Build and deploy machine learning solutions on Vertex ai

Ending

I hope that working through these courses and the labs that are part of these courses will help you gain a good understanding of building and deploying machine learning solutions with Vertex ai.

If you are looking for a complete bootcamp to learn MLOP, you can check out DataTalks.Club's MLOps Zoomcamp. You can learn more about this bootcamp in The Only Free Course You Need to Become a Professional MLOps Engineer.

twitter.com/balawc27″ rel=”noopener”>Bala Priya C. is an Indian developer and technical writer. He enjoys working at the intersection of mathematics, programming, data science, and content creation. His areas of interest and expertise include DevOps, data science, and natural language processing. He likes to read, write, code and drink coffee! Currently, he is working to learn and share his knowledge with the developer community by creating tutorials, how-to guides, opinion pieces, and more. Bala also creates engaging resource descriptions and coding tutorials.