We may earn an affiliate commission when you visit our partners.
Google Cloud Training
Register for this course and see more details by visiting:
OpenCourser.com/course/y6hxua/trabalhar
Here's a deal for you
Save money when you learn with a deal that may be relevant to this course.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Get offer
What's inside
Syllabus
Save this course
Create your own learning path.
Save this course to your list so you can find it easily later.
Save
Save
Activities
Coming soon
We're preparing activities for
Trabalhar com Notebooks na Vertex AI.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Trabalhar com Notebooks na Vertex AI will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/y6hxua/trabalhar
Reading list
We haven't picked any books for this reading list yet.
Provides a practical guide to machine learning for hackers. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about machine learning.
Provides a practical guide to machine learning with Scikit-Learn, Keras, and TensorFlow. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about machine learning.
Provides a comprehensive overview of machine learning. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about machine learning.
Provides a comprehensive overview of machine learning with Python. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about machine learning.
Save
Provides a comprehensive overview of machine learning. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about machine learning.
Provides a comprehensive overview of machine learning with TensorFlow, covering both the theoretical and practical aspects of the topic. It great resource for beginners who want to learn about machine learning and TensorFlow.
Save
Provides a comprehensive overview of deep learning with Python. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about deep learning.
Provides a comprehensive overview of machine learning with R. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about machine learning.
Save
Provides a comprehensive overview of deep learning. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about deep learning.
Provides a comprehensive overview of machine learning with Python. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about machine learning.
Provides a comprehensive overview of machine learning with R. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about machine learning.
Provides a comprehensive overview of machine learning with Java. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about machine learning.
Provides a comprehensive overview of pattern recognition and machine learning. It covers the theoretical and practical aspects of the topic, and it great resource for beginners who want to learn about pattern recognition and machine learning.
A specialized guide to using Jupyter Notebooks for machine learning tasks, covering topics such as data preprocessing, model training, and evaluation.
A practical guide to using Jupyter Notebooks for data analysis and visualization, covering topics such as data cleaning, data manipulation, and interactive visualizations.
A practical handbook focusing on data science applications of Jupyter Notebooks, including data cleaning, exploratory data analysis, machine learning, and data visualization. Assumes some prior programming knowledge.
Save
A guide to using Jupyter Notebooks for Python developers, covering topics such as data analysis, machine learning, and web development.
Provides a comprehensive overview of the machine learning workflow using popular Python libraries such as Scikit-Learn, Keras, and TensorFlow. It practical guide that can be used by data scientists and machine learning engineers of all levels.
Presents a collection of design patterns that can be used to solve common problems in machine learning. It provides a systematic approach to designing and developing machine learning systems.
Covers the machine learning workflow from a software engineering perspective. It provides guidance on how to design, develop, and deploy machine learning systems in a scalable and maintainable way.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/y6hxua/trabalhar
Share
Similar courses
Similar courses are unavailable at this time. Please try again later.
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Session
October 27, 2025
- November 10, 2025
Language
pt-BR
Transcript
English
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2025 OpenCourser