Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required. 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 using Vertex AI. Learners will get hands-on experience building machine learning models on Google Cloud using QwikLabs.
Offered By
Google CloudAbout this Course
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Flexible deadlines
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Shareable Certificate
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Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Intermediate Level
Approx. 6 hours to complete
English
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will 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 AutoML.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Intermediate Level
Approx. 6 hours to complete
English
Could your company benefit from training employees on in-demand skills?
Try Coursera for Business
Offered by
Syllabus - What you will learn from this course
1 minute to complete
Introduction
1 minute to complete
1 video (Total 1 min)
12 minutes to complete
Introduction to Analytics and AI
12 minutes to complete
4 videos (Total 8 min)
1 hour to complete
Prebuilt ML model APIs for Unstructured Data
1 hour to complete
5 videos (Total 13 min)
1 hour to complete
Big Data Analytics with Notebooks
1 hour to complete
4 videos (Total 7 min)
1 hour to complete
Production ML Pipelines
1 hour to complete
6 videos (Total 9 min)
2 hours to complete
Custom Model building with SQL in BigQuery ML
2 hours to complete
6 videos (Total 12 min)
28 minutes to complete
Custom Model Building with AutoML
28 minutes to complete
6 videos (Total 24 min)
1 minute to complete
Summary
1 minute to complete
1 video (Total 1 min)
Reviews
- 5 stars69.02%
- 4 stars23.97%
- 3 stars4.43%
- 2 stars1.45%
- 1 star1.10%
TOP REVIEWS FROM SMART ANALYTICS, MACHINE LEARNING, AND AI ON GOOGLE CLOUD
by ACMar 30, 2021
Great hands one excercises to confirm few coding lines to do real world predictions
by MCAug 21, 2022
A general introduction for enabling data engineer start working on GCP
by PRJan 23, 2020
I couldn't complete the Kubeflow lab due to issues that I encountered setting it up. Overall, the course has given me a good understanding of Machine Learning model creation options available on GCP
by JAFeb 2, 2022
Great insight about using machine learning on Google cloud platform. I am impressed
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