Machine Learning on Google Cloud
Virtual Instructor-Led Training
5 Days (40 Hours)The Machine Learning on Google Cloud course teaches participants how to build and deploy machine learning models on Google Cloud using tools such as AI Platform and BigQuery ML.
Course Objectives
- Build, train, and deploy a machine learning model without writing a single line of code using Vertex AI AutoML
- Understand when to use AutoML and Big Query ML
- Create Vertex AI managed datasets
- Add features to a Feature Store
- Describe Analytics Hub, Dataplex, and Data Catalog
Upcoming Schedules
Who should attend Machine Learning on Google Cloud Course
- Data Engineer
- Data Analyst
- Data Scientist
Machine Learning on Google Cloud Course Prerequisites
Recommended
- Basic proficiency with a scripting language, preferably Python
- Some familiarity with basic machine learning concepts
Machine Learning on Google Cloud Course Outline
- Describe the Vertex AI Platform and how it is used to quickly build, train, and deploy AutoML machine learning models without writing a single line of code
- Describe best practices for implementing machine learning on Google Cloud
- Develop a data strategy around machine learning
- Examine use cases that are then reimagined through an ML lens
- Leverage Google Cloud Platform tools and environment to do ML
- Learn from Google's experience to avoid common pitfalls
- Carry out data science tasks in online collaborative notebooks
FAQ on Machine Learning on Google Cloud Course
Is Google Cloud machine learning certification worth it?
Yes, the Google Cloud Professional Machine Learning Engineer certification can be a worthwhile investment for those working in or aspiring to work in machine learning roles on the Google Cloud Platform. It demonstrates expertise in designing, implementing, and maintaining ML solutions within Google Cloud, and is often favored by employers.
What is machine learning in Google Cloud?
In Google Cloud, machine learning (ML) refers to the suite of services and tools that allow users to build, deploy, and manage ML models, leveraging Google's infrastructure and expertise. Google Cloud provides a comprehensive platform for both experts and those with limited ML experience to utilize ML for various applications.
What is the salary of a Google machine learning engineer?
The typical pay range is between $244K - $367K/yr[1]. This is based on 7917 salaries submitted by Google Machine Learning Engineer professionals on Glassdoor, as of June 2025.
Who should take this GCP Machine learning training?
This GCP Machine Learning training is ideal for individuals aiming to enhance their skills in building, deploying, and managing machine learning models on Google Cloud Platform. It is particularly beneficial for professionals in roles such as Data Engineer, Data Analyst, and Data Scientist, as well as those seeking to enter the artificial intelligence and data science sector. This course is also suitable for anyone looking to gain a comprehensive understanding of TensorFlow, Vertex AI, AutoML, and end-to-end ML pipelines and achieve Google Cloud Professional Machine Learning Engineer certification.
Does this Machine Learning on Google Cloud course provide hands-on labs or practical exercises?
Yes, this Machine Learning on Google Cloud course includes 40 hours of hands-on labs and practical exercises. These sessions are designed to provide real-world experience in Vertex AI, TensorFlow, BigQuery ML, and AutoML, allowing you to apply theoretical knowledge to practical scenarios. You will work on building, training, and deploying machine learning models, performing data preprocessing, and running predictive analytics on large datasets to reinforce your learning.