Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
Smart Analytics, Machine Learning, and AI on Google Cloud
Smart Analytics, Machine Learning, and AI on Google Cloud
This course is part of multiple programs.
Instructor: Google Cloud Training
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
7 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Differentiate between ML, AI and deep learning.
Discuss the use of ML API’s on unstructured data.
Execute BigQuery commands from notebooks.
Create ML models by using SQL syntax in BigQuery and without coding using Vertex AI AutoML.
Skills you'll gain
Tools you'll learn
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Assessments
6 assignments
Taught in English
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This course is available as part of
When you enroll in this course, you'll also be asked to select a specific program.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 8 modules in this course
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