About this Course
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Flexible deadlines

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Intermediate Level

Approx. 12 hours to complete

Suggested: 1 week of study, 6-10 hours/week...

English

Subtitles: English

Skills you will gain

TensorflowBigqueryGoogle Cloud PlatformCloud Computing

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

Suggested: 1 week of study, 6-10 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
3 hours to complete

Introduction to the Data and Machine Learning on Google Cloud Platform Specialization .

13 videos (Total 78 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 Storage5m
Build on Google's Global Network3m
Security: On-premise vs Cloud-native2m
Evolution of Google Cloud Big Data Tools5m
Getting Started with Google Cloud Platform and Qwiklabs3m
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

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 with BigQuery ML

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
BigQueryML: 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
2 hours to complete

Create Streaming Data Pipelines with Cloud Pub/sub and Cloud Dataflow

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 Review4m
2 hours to complete

Classify Images with Pre-Built Models using Vision API and Cloud AutoML

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

1 video (Total 5 min)
1 video
4.6
1231 ReviewsChevron Right

45%

started a new career after completing these courses

43%

got a tangible career benefit from this course

Top reviews from Google Cloud Platform Big Data and Machine Learning Fundamentals

By VSMar 3rd 2019

Overall a good curated course to help understand the GCP offerings and high level architecture of how their offerings fit in the current landscape. Easy to follow along as this was fundamental course.

By ARMay 27th 2019

This course gives you a pretty good fundamental idea on what you are diving into. Google cloud platform has bucket of data engineering features. This course sets you on the starting line for them.

About Google Cloud

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success....

About the Data Engineering, Big Data, and Machine Learning on GCP Specialization

This five-week, accelerated online specialization provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The course covers structured, unstructured, and streaming data. This course teaches the following skills: • Design and build data processing systems on Google Cloud Platform • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc • Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow • Derive business insights from extremely large datasets using Google BigQuery • Train, evaluate and predict using machine learning models using Tensorflow and Cloud ML • Enable instant insights from streaming data This class is intended for developers who are responsible for: • Extracting, Loading, Transforming, cleaning, and validating data • Designing pipelines and architectures for data processing • Creating and maintaining machine learning and statistical models • Querying datasets, visualizing query results and creating reports >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<...
Data Engineering, Big Data, and Machine Learning on GCP

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following:

    • A common query language such as SQL

    • Extract, transform, load activities

    • Data modeling

    • Machine learning and/or statistics

    • Programming in Python

  • To be eligible for the free trial, you will need:

    - Google account (Google is currently blocked in China)

    - Credit card or bank account

    - Terms of service

    Note: There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as "business" status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602

    More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/

    For more details on how the free trial works, visit our documentation page: https://cloud.google.com/free-trial/docs/

  • If your current Google account is no longer eligible for the Google Cloud Platform free trial, you can create another Google account. Your new Google account should be used to sign up for the free trial.

  • View this page for more details: https://cloud.google.com/free-trial/docs/

  • Yes, this online course is based on the instructor-led training formerly known as CPB100.

  • The course covers the topics presented on the certification exam, however we recommend additional preparation including hands-on product experience. The best preparation for certification is real-world, hands-on experience. Review the Google Certified Professional Data Engineer certification preparation guide for further information and resources at https://cloud.google.com/certification/guides/data-engineer/

  • Google’s Certification Program gives customers and partners a way to demonstrate their technical skills in a particular job-role and technology. Individuals are assessed using a variety of rigorously developed industry-standard methods to determine whether they meet Google’s proficiency standards. Read more at https://cloud.google.com/certification/

More questions? Visit the Learner Help Center.