Google Cloud
Google Cloud Big Data and Machine Learning Fundamentals
Google Cloud

Google Cloud Big Data and Machine Learning Fundamentals

321,722 already enrolled

Gain insight into a topic and learn the fundamentals.
4.7

(16,046 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 9 hours
Learn at your own pace
95%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.7

(16,046 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.

Details to know

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Assessments

5 quizzes

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 quiz1 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 quiz1 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 quiz1 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 quiz

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 quiz1 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 (2,753 ratings)
Google Cloud Training
Google Cloud
1,593 Courses2,698,360 learners

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Google Cloud

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4.7

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