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⇱ Smart Analytics, Machine Learning, and AI on Google Cloud | Coursera

Smart Analytics, Machine Learning, and AI on Google Cloud

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Smart Analytics, Machine Learning, and AI on Google Cloud

This course is part of multiple programs.

41,289 already enrolled

Included with

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Gain insight into a topic and learn the fundamentals.
4.6

1,247 reviews

Intermediate level
Some related experience required
Flexible schedule
7 hours to complete
Learn at your own pace
86%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.6

1,247 reviews

Intermediate level
Some related experience required
Flexible schedule
7 hours to complete
Learn at your own pace
86%
Most learners liked this course

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.

Details to know

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Assessments

6 assignments

Taught in English

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  • 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

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.

In this module, we introduce the course and agenda

What's included

1 video

1 video•Total 1 minute
  • Course Introduction•1 minute

This modules talks about ML options on Google Cloud

What's included

4 videos1 assignment

4 videos•Total 8 minutes
  • Module introduction•0 minutes
  • What is AI?•5 minutes
  • From ad-hoc data analysis to data-driven decisions•1 minute
  • Options for ML models on Google Cloud•1 minute
1 assignment•Total 4 minutes
  • Introduction to Analytics and AI•4 minutes

This module focuses on using pre-built ML APIs on your unstructured data

What's included

5 videos1 assignment1 app item

5 videos•Total 13 minutes
  • Module introduction•0 minutes
  • Unstructured data is hard•3 minutes
  • ML APIs for enriching data•4 minutes
  • Lab Intro: Using the Natural Language API to Classify Unstructured Text•1 minute
  • Getting Started with Google Cloud and Qwiklabs•5 minutes
1 assignment•Total 4 minutes
  • Prebuilt ML model APIs for Unstructured Data•4 minutes
1 app item•Total 60 minutes
  • Using the Natural Language API to Classify Unstructured Text•60 minutes

This module covers how to use Notebooks

What's included

4 videos1 assignment1 app item

4 videos•Total 7 minutes
  • Module introduction•0 minutes
  • What’s a Notebook?•5 minutes
  • BigQuery magic and ties to Pandas•2 minutes
  • Lab Intro: BigQuery in JupyterLab on Vertex AI•0 minutes
1 assignment•Total 4 minutes
  • Big Data Analytics with AI Platform Notebooks•4 minutes
1 app item•Total 60 minutes
  • BigQuery in JupyterLab on Vertex AI•60 minutes

This module covers building custom ML models and introduces Vertex AI and TensorFlow Hub

What's included

6 videos1 assignment1 app item

6 videos•Total 8 minutes
  • Module introduction•1 minute
  • Ways to do ML on Google Cloud•1 minute
  • Vertex AI Pipelines•4 minutes
  • TensorFlow Hub•1 minute
  • Lab Intro: Running Pipelines on Vertex AI•0 minutes
  • Summary•0 minutes
1 assignment•Total 4 minutes
  • Production ML Pipelines•4 minutes
1 app item•Total 60 minutes
  • Lab: Running Pipelines on Vertex AI•60 minutes

This module covers BigQuery ML

What's included

6 videos1 assignment2 app items

6 videos•Total 12 minutes
  • Module introduction•0 minutes
  • BigQuery ML for Quick Model Building•4 minutes
  • Supported models•7 minutes
  • Lab Intro: Predict Bike Trip Duration with a Regression Model in BigQuery ML•0 minutes
  • Lab Intro: Movie Recommendations in BigQuery ML•0 minutes
  • Summary•0 minutes
1 assignment•Total 4 minutes
  • Custom Model building with SQL in BigQuery ML•4 minutes
2 app items•Total 120 minutes
  • Predict Bike Trip Duration with a Regression Model in BigQuery ML•60 minutes
  • Movie Recommendations in BigQuery ML•60 minutes

Custom model building with Vertex AI AutoML

What's included

6 videos1 assignment

6 videos•Total 23 minutes
  • Module introduction•1 minute
  • Why AutoML?•11 minutes
  • AutoML Vision•2 minutes
  • AutoML Natural Language Processing•3 minutes
  • AutoML Tables•6 minutes
  • Summary•0 minutes
1 assignment•Total 4 minutes
  • Custom Model Building with AutoML•4 minutes

This module recaps the topics covered in the course

What's included

1 video

1 video•Total 1 minute
  • Course Summary•1 minute

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Instructor

Instructor ratings
4.6 (162 ratings)
Google Cloud
2,244 Courses•4,416,115 learners

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Learner reviews

  • 5 stars

    69.44%

  • 4 stars

    23.65%

  • 3 stars

    4.33%

  • 2 stars

    1.44%

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Showing 3 of 1247

DZ
·

Reviewed on Apr 18, 2020

Very good course to experience all the diverse offerings for ML on GCP.

VR
·

Reviewed on Feb 28, 2021

Amazing to be part of this great learning Journey!! I am learning concepts and strong fundamentals to build a good foundation.

MA
·

Reviewed on May 11, 2020

Content was fun and exciting but some exercises/graded labs inside this course are very unclear with the instructions and also took a long time to finish (model training).

Frequently asked questions

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

This course is currently available only to learners who have paid or received financial aid, when available.

Financial aid available,