About this Course

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Learner Career Outcomes

41%

started a new career after completing these courses

39%

got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 12 hours to complete
English

What you will learn

  • Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud.

  • Use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud.

  • Employ BigQuery to carry out interactive data analysis.

  • Choose between different data processing products on Google Cloud.

Skills you will gain

TensorflowBigqueryGoogle Cloud PlatformCloud Computing

Learner Career Outcomes

41%

started a new career after completing these courses

39%

got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 12 hours to complete
English

Instructor

Offered by

Placeholder

Google Cloud

Syllabus - What you will learn from this course

Content RatingThumbs Up95%(22,665 ratings)Info
Week
1

Week 1

3 hours to complete

Introduction to the Data and Machine Learning on Google Cloud Course

3 hours to complete
13 videos (Total 80 min), 2 readings, 2 quizzes
13 videos
Introduction to Google Cloud Platform3m
Compute Power for Analytic and ML Workloads9m
Demo: Creating a VM on Compute Engine13m
Elastic Storage with Google Cloud Storage6m
Build on Google's Global Network3m
Security: On-premise vs Cloud-native2m
Evolution of Google Cloud Big Data Tools5m
Getting Started with Google Cloud and Qwiklabs4m
Choosing the right approach5m
What you can do with Google Cloud Platform3m
Activity: Explore real customer solution architectures7m
Key roles in a data-driven organization6m
2 readings
Google Cloud Public Datasets program10m
Module Resources10m
1 practice exercise
Module Review5m
2 hours to complete

Recommending Products using Cloud SQL and Spark

2 hours to complete
8 videos (Total 50 min), 1 reading, 2 quizzes
8 videos
Introduction to machine learning5m
Challenge: ML for recommending housing rentals8m
Approach: Move from on-premise to Google Cloud Platform9m
Demo: From zero to an Apache Spark job in 10 minutes or less6m
Challenge: Utilizing and tuning on-premise clusters6m
Move storage off-cluster with Google Cloud Storage4m
Lab Intro2m
1 reading
Module Resources5m
1 practice exercise
Module Review15m
3 hours to complete

Predict Visitor Purchases Using BigQuery ML

3 hours to complete
13 videos (Total 74 min), 2 readings, 2 quizzes
13 videos
Demo: Query 2 billion lines of Github code in less than 30 seconds11m
BigQuery: Fast SQL Engine4m
Demo: Exploring bike share data with SQL11m
Data quality4m
BigQuery managed storage5m
Insights from geographic data2m
Demo: Analyzing lightning strikes with BigQuery GIS7m
Choosing a ML model type for structured data4m
Predicting customer lifetime value5m
BigQuery ML: Create models with SQL3m
Phases in ML model lifecycle2m
BigQuery ML: key features walkthrough5m
2 readings
Lab Intro10m
Module Resources10m
1 practice exercise
Module Review4m
Week
2

Week 2

2 hours to complete

Real-time IoT Dashboards with Pub/Sub, Dataflow, and Data Studio

2 hours to complete
8 videos (Total 31 min), 1 reading, 2 quizzes
8 videos
Message-oriented architectures with Cloud Pub/Sub6m
Designing streaming pipelines with Apache Beam3m
Implementing streaming pipelines on Cloud Dataflow3m
Visualizing insights with Data Studio3m
Creating charts with Data Studio2m
Demo: Data Studio walkthrough7m
Lab Intro1m
1 reading
Module Resources10m
1 practice exercise
Module Review30m
2 hours to complete

Deriving Insights from Unstructured Data using Machine Learning

2 hours to complete
10 videos (Total 55 min), 2 readings, 2 quizzes
10 videos
How does ML on unstructured data work?3m
Demo: ML built into Google Photos1m
Comparing approaches to ML2m
Demo: Using ML building blocks7m
Using pre-built AI to create a chatbot4m
Customizing Pre-built models with AutoML7m
Lab Intro22s
Building a Custom Model1m
Demo: Text classification done three ways21m
2 readings
Additional resources to build custom models10m
Module Resources10m
1 practice exercise
Module Review
5 minutes to complete

Summary

5 minutes to complete
1 video (Total 5 min)
1 video

Reviews

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