Google Cloud
Introduction to AI and Machine Learning on Google Cloud
Google Cloud

Introduction to AI and Machine Learning on Google Cloud

This course is part of Preparing for Google Cloud Certification: Machine Learning Engineer Professional Certificate

Taught in English

Some content may not be translated

9,492 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.7

(56 reviews)

Beginner level
No prior experience required
9 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Recognize the data-to-AI technologies and tools offered by Google Cloud.

  • Use generative AI capabilities in applications.

  • Choose between different options to develop an AI project on Google Cloud.

  • Build ML models end-to-end by using Vertex AI.

Details to know

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Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.7

(56 reviews)

Beginner level
No prior experience required
9 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your Cloud Computing expertise

This course is part of the Preparing for Google Cloud Certification: Machine Learning Engineer Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
  • 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 from Google Cloud
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There are 6 modules in this course

This module covers the course objective of helping learners navigate the AI development tools on Google Cloud. It also provides an overview of the course structure, which is based on a three-layer AI framework including AI foundations, development, and solutions.

What's included

1 video

This module begins with a use case demonstrating the AI capabilities. It then focuses on the AI foundations including cloud infrastructure like compute and storage. It also explains the primary data and AI development products on Google Cloud. Finally, it demonstrates how to use BigQuery ML to build an ML model, which helps transition from data to AI.

What's included

10 videos1 reading1 quiz1 app item

This module explores the various options for developing an ML project on Google Cloud, from ready-made solutions like pre-trained APIs, to no-code and low-code solutions like AutoML, and code-based solutions like custom training. It compares the advantages and disadvantages of each option to help decide the right development tools.

What's included

8 videos1 reading1 quiz1 app item

This module walks through the ML workflow from data preparation, to model development, and to model serving on Vertex AI. It also illustrates how to convert the workflow into an automated pipeline using Vertex AI Pipelines.

What's included

9 videos1 reading1 quiz1 app item

This module introduces generative AI (gen AI), the newest advancement in AI, and the essential toolkits for developing gen AI projects. It starts by examining the gen AI workflow on Google Cloud. It then investigates how to use Gen AI Studio and Model Garden to access Gemini multimodal, design prompt, and tune models. Finally, it explores the built-in gen AI capabilities of AI solutions.

What's included

9 videos1 reading1 quiz1 app item

This module provides a summary of the entire course by covering the most important concepts, tools, technologies, and products.

What's included

1 video1 reading

Instructor

Instructor ratings
4.8 (7 ratings)
Google Cloud Training
Google Cloud
1,464 Courses2,606,336 learners

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Google Cloud

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4.7

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Reviewed on May 14, 2024

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