This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
Google Cloud Big Data and Machine Learning Fundamentals
Google Cloud Big Data and Machine Learning Fundamentals
This course is part of multiple programs.
Instructor: Google Cloud Training
323,906 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.7
(16,139 reviews)
Beginner level
No prior experience required
Flexible schedule
Approx. 9 hours
Learn at your own pace
95%
Most learners liked this course
What you'll learn
Identify the data-to-AI lifecycle on Google Cloud and the major products of big data and machine learning.
Design streaming pipelines with Dataflow and Pub/Sub and dDesign streaming pipelines with Dataflow and Pub/Sub.
Identify different options to build machine learning solutions on Google Cloud.
Describe a machine learning workflow and the key steps with Vertex AI and build a machine learning pipeline using AutoML.
Skills you'll gain
Details to know
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Assessments
5 assignments
Taught in English
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There are 7 modules in this course
This section welcomes learners to the Big Data and Machine Learning Fundamentals course, and provides an overview of the course structure and goals.
What's included
2 videos
This section explores the key components of Google Cloud's infrastructure. It's here that we introduce many of the big data and machine learning products and services that support the data-to AI lifecycle on Google Cloud.
What's included
10 videos1 reading1 assignment1 app item
This section introduces Google Cloud's solution to managing streaming data. It examines an end-to-end pipeline, including data ingestion with Pub/Sub, data processing with Dataflow, and data visualization with Looker and Looker Studio.
What's included
9 videos1 reading1 assignment1 app item
This section introduces learners to BigQuery, Google's fully-managed, serverless data warehouse. It also explores BigQuery ML, and the processes and key commands that are used to build custom machine learning models.
What's included
9 videos1 reading1 assignment1 app item
This section explores four different options to build machine learning models on Google Cloud. It also introduces Vertex AI, Google's unified platform for building and managing the lifecycle of ML projects.
What's included
8 videos1 reading1 assignment
This section focuses on the three key phases--data preparation, model training, and model preparation--of the machine learning workflow in Vertex AI. Learners get the opportunity to practice building a machine learning model with AutoML.
What's included
8 videos1 reading1 assignment1 app item
This section reviews the topics covered in the course, and provides additional resources for further learning.
What's included
1 video
Instructor
Instructor ratings
4.7 (2,783 ratings)Offered by
Recommended if you're interested in Machine Learning
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Learner reviews
4.7
16,139 reviews
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Showing 3 of 16139
AD
5
Reviewed on Sep 23, 2019
This course really helped me in understanding exactly 'How the Big data and Machine learning can be used in Cloud' and 'The ease to use it'. Thank you for summing all the fundamentals in this course.
IS
5
Reviewed on Nov 29, 2020
In this course I have learned many things many new things which I was unaware of. Thanks coursera for providing such a great platform to students like me to learn and educate ourself for the future
VS
5
Reviewed on Mar 2, 2019
Overall a good curated course to help understand the GCP offerings and high level architecture of how their offerings fit in the current landscape. Easy to follow along as this was fundamental course.
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Frequently asked questions
Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following:
• A common query language such as SQL
• Extract, transform, load activities
• Data modeling
• Machine learning and/or statistics
• Programming in Python
To be eligible for the free trial, you will need:
- Google account (Google is currently blocked in China)
- Credit card or bank account
- Terms of service
Note: There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as "business" status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602
More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/
For more details on how the free trial works, visit our documentation page: https://cloud.google.com/free-trial/docs/
If your current Google account is no longer eligible for the Google Cloud Platform free trial, you can create another Google account. Your new Google account should be used to sign up for the free trial.