What are best practices for implementing machine learning on Google Cloud? What is Vertex AI and how can you use the platform to quickly build, train, and deploy AutoML machine learning models without writing a single line of code? What is machine learning, and what kinds of problems can it solve?
How Google does Machine Learning
About this Course
What you will learn
Describe Vertex AI Platform and how it's 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
Leverage Google Cloud Platform tools and environment to do ML
Articulate Responsible AI best practices
Skills you will gain
- Application Programming Interfaces (API)
- Inclusive ML
- Machine Learning
- Google Cloud Platform
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Syllabus - What you will learn from this course
Introduction to Course and Series
This module introduces the course series and the Google experts who will be teaching it.
What It Means to be AI-First
In this module, you explore building a data strategy around machine learning.
How Google Does ML
This module shares the organizational know-how Google has acquired over the years.
Machine Learning Development with Vertex AI
All machine learning starts with some type of goal - whether it be a business use case, academic use case, or goal you are trying to solve. This module reviews the process of determining whether the model is ready for production the “proof of concept” or “experimentation” phase.
Machine Learning Development with Vertex Notebooks
This module explores both managed notebooks and user-managed notebooks for machine learning development in Vertex AI.
Best Practices for Implementing Machine Learning on Vertex AI
This module reviews best practices for a number of different machine learning processes in Vertex AI.
Responsible AI Development
This module discusses why machine learning systems aren’t fair by default and some of the things you have to keep in mind as you infuse ML into your products.
This module is a summary of the How Google Does Machine Learning course.
- 5 stars68.97%
- 4 stars23.71%
- 3 stars5.25%
- 2 stars1.13%
- 1 star0.91%
TOP REVIEWS FROM HOW GOOGLE DOES MACHINE LEARNING
An excellent overview providing a birds-eye view of where ML fits in the larger scheme of a software project and how it evolves. It also provides a good introduction to leveraging Google's ML APIs.
be more interactive, and hands on. I found too much was spoon-fed in the labs. More exploration should be encouraged.
Machine Learning API's were really cool stuff to learn and see the examples running.
Though a little more emphasis is needed to understand the codes used in the final lab session :)
This is a good introductory course on how actually Machine Learning is being developed in Companies like Google. It covers the basic aspects of how ML is done using Cloud Platform using Cloud APIs.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
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The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
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Last Updated: September 1, 2015
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