07

Smart Analytics, Machine Learning, and AI on Google Cloud

07

Smart Analytics, Machine Learning, and AI on Google Cloud

40 hours Introductory universal_currency_alt 25 Credits

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.

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Course Info
Objectives
  • 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.
  • Create ML models without coding using AutoML.
Prerequisites
To benefit from this course, participants should have completed “Google Cloud Big Data and Machine Learning Fundamentals” or have equivalent experience.
Audience
Data Engineers
Available languages
English
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After finishing this course, you can explore additional content in your learning path or browse the catalog.
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Interested in taking this course with one of our authorized on-demand partners?
Explore Google Cloud content on Coursera and Pluralsight.
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View the public classroom schedule here.
Can I take this course for free?
When you enroll into most courses, you will be able to consume course materials like videos and documents for free. If a course consists of labs, you will need to purchase an individual subscription or credits to be able consume the labs. Labs can also be unlocked by any campaigns you participate in. All required activities in a course must be completed to be awarded the completion badge.
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