We may earn an affiliate commission when you visit our partners.
Google Cloud Training
This course covers designing and building a TensorFlow input data pipeline, building ML models with TensorFlow and Keras, improving the accuracy of ML models, writing ML models for scaled use, and writing specialized ML models.
Register for this course and see more details by visiting:
OpenCourser.com/course/sj924z/tensorflow
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
Introduction to the Course
This module provides an overview of the course and its objectives.
Introduction to the TensorFlow Ecosystem
This module introduces the TensorFlow framework and previews its main components as well as the overall API hierarchy.
Read more
Syllabus
Introduction to the Course
This module provides an overview of the course and its objectives.
Introduction to the TensorFlow Ecosystem
This module introduces the TensorFlow framework and previews its main components as well as the overall API hierarchy.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Deepens knowledge and skills in machine learning techniques and tools
Suitable for learners with an understanding of machine learning fundamentals
Offers hands-on labs and interactive materials for practical learning
Provides a strong foundation in TensorFlow and Keras for implementing ML models
Taught by Google Cloud Training, with expertise in machine learning and TensorFlow
Save this course
Create your own learning path.
Save this course to your list so you can find it easily later.
Save
Save
Reviews summary
Practical tensorflow on google cloud
According to learners, this course provides a practical and relevant introduction to using TensorFlow on Google Cloud. Students found the hands-on labs and exercises to be particularly useful for applying concepts, though a few noted minor glitches or debugging challenges. The course offers clear explanations of key topics like the Keras API and data pipelines. While some learners felt the pacing was fast or the content basic if they had prior TensorFlow knowledge, most appreciated the solid overview and coverage of essential GCP services like Vertex AI for training at scale. Overall, students report a largely positive experience.
Pacing/depth varies for learners.
"Some parts moved a bit fast, especially if you needed more background on underlying concepts."
"Felt a bit basic if you already know TensorFlow, but it was a good overview of GCP integration."
"Good overview, though some advanced topics like model optimization could go deeper."
"The pace was just right for getting a solid introduction, but might require supplementary learning for mastery."
Core concepts explained effectively.
"The Keras API explanation was clear and easy to follow, even for someone relatively new."
"Explanations for building input data pipelines with tf.data were particularly clear and insightful."
"I appreciated the clear breakdown of complex topics into manageable modules."
"The instructors explained concepts in a way that made them easy to grasp and apply."
Labs are useful for practical skills.
"Labs worked well and reinforced the concepts taught in the lectures."
"Hands-on exercises were the best part of the course for me, allowing me to apply theory immediately."
"The labs provided valuable practical experience with Vertex AI and data pipelines."
"I found the guided labs very helpful in understanding the workflow on Google Cloud."
Highly relevant for ML on GCP jobs.
"Very relevant content for my job, immediately applicable to building ML solutions on Google Cloud."
"Perfect for getting started with ML on Google Cloud, covering services needed for a real project."
"Covers essential GCP services for ML practitioners looking to deploy and scale models."
"The course provides practical insights into using TensorFlow effectively within the GCP ecosystem."
Labs occasionally have glitches.
"Labs were sometimes frustrating to debug when they didn't work as expected."
"Experienced minor glitches with the lab environment that took time to resolve."
"The labs didn't work for me initially and required troubleshooting that wasn't covered."
"While generally good, I encountered occasional technical hurdles with the lab setup."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in TensorFlow on Google Cloud with these
activities:
Write a Blog Post on Your TensorFlow Project
Show steps
Solidify your understanding of TensorFlow by documenting your learning and insights through a blog post that showcases your project.
Show steps
-
Choose a project you've built using TensorFlow
-
Write about the problem you solved, the approach you took, and the results you obtained
-
Share your code and any resources you used
-
Publish your blog post on a platform like Medium or DEV.to
Show all one activities
Write a Blog Post on Your TensorFlow Project
Show steps
Solidify your understanding of TensorFlow by documenting your learning and insights through a blog post that showcases your project.
Show steps
Show steps
Show steps
- Choose a project you've built using TensorFlow
- Write about the problem you solved, the approach you took, and the results you obtained
- Share your code and any resources you used
- Publish your blog post on a platform like Medium or DEV.to
Show all one activities
Career center
Learners who complete TensorFlow on Google Cloud will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models, working closely with data scientists and software engineers. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Machine Learning Engineers develop the skills they need to design and build scalable machine learning models.
Data Scientist
Data Scientist
Data Scientists use machine learning to solve business problems. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Data Scientists develop the skills they need to design and build scalable machine learning models for real-world applications.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Software Engineers develop the skills they need to integrate machine learning into their software applications.
Solutions Architect
Solutions Architect
Solutions Architects design and implement cloud-based solutions. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework, and how to use it on Google Cloud Platform. This course will help Solutions Architects develop the skills they need to design and implement scalable machine learning solutions for their customers.
Product Manager
Product Manager
Product Managers develop and manage software products. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Product Managers understand how machine learning can be used to improve their products.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make better decisions. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Data Analysts develop the skills they need to use machine learning to analyze data and solve business problems.
Business Analyst
Business Analyst
Business Analysts help businesses identify and solve problems. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Business Analysts develop the skills they need to use machine learning to solve business problems.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Quantitative Analysts develop the skills they need to use machine learning to analyze financial data and make investment decisions.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Operations Research Analysts develop the skills they need to use machine learning to solve business problems.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to help businesses make better decisions. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Statisticians develop the skills they need to use machine learning to analyze data and solve business problems.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers develop new machine learning algorithms and techniques. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Machine Learning Researchers develop the skills they need to use TensorFlow to conduct research and develop new machine learning algorithms.
Computer Scientist
Computer Scientist
Computer Scientists design and develop computer systems. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Computer Scientists develop the skills they need to use TensorFlow to develop machine learning applications.
Software Developer
Software Developer
Software Developers design, develop, and maintain software applications. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Software Developers develop the skills they need to use TensorFlow to develop machine learning applications.
Web Developer
Web Developer
Web Developers design and develop websites. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Web Developers develop the skills they need to use TensorFlow to develop machine learning applications for the web.
Data Engineer
Data Engineer
Data Engineers build and maintain data pipelines. TensorFlow on Google Cloud provides a comprehensive overview of TensorFlow, the leading open-source machine learning framework. This course will help Data Engineers develop the skills they need to use TensorFlow to build and maintain data pipelines for machine learning applications.
For more career information including salaries, visit:
OpenCourser.com/course/sj924z/tensorflow
Reading list
We've selected six books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
TensorFlow on Google Cloud.
This course uses TensorFlow and Keras, both of which are from François Chollet. Chollet wrote this book as a practical guide to building neural networks using TensorFlow and Keras. It can be used as a supplemental text with this course to provide even more context for the concepts being taught.
Covers building ML models with Python, including TensorFlow and Keras. It can be used as a supplemental resource to this course to provide more context for the concepts being taught.
Introduces the fundamentals of deep learning using fastai and PyTorch. It can be used as a companion to this course to provide more context for the concepts being taught.
Is an introduction to deep learning that uses a conceptual approach. It can be used as a supplement to this course to provide a more accessible introduction to deep learning.
Provides a practical guide to building deep learning models using TensorFlow 2 and Keras. It can be used as a supplemental resource to this course to provide more context for the concepts being taught.
Provides a comprehensive introduction to machine learning using TensorFlow. It can be used as a supplemental resource to this course to provide more context for the concepts being taught.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/sj924z/tensorflow
Share
Similar courses
Similar courses are unavailable at this time. Please try again later.
Rating
4.4
Effort
Approx. 13 hours
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
This course belongs to a
collection
called
Machine Learning on Google Cloud. It's comprised of seven courses:
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