This 2-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.
Offered By
Google CloudAbout this Course
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Learner Career Outcomes
41%
started a new career after completing these courses
40%
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
Subtitles: French, Portuguese (Brazilian), Russian, English, Spanish
What you will learn
Processing big data at scale for analytics and machine learning
Fundamentals of building new machine learning models
Creating streaming data pipelines and dashboards
Skills you will gain
TensorflowBigqueryGoogle Cloud PlatformCloud Computing
Learner Career Outcomes
41%
started a new career after completing these courses
40%
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
Subtitles: French, Portuguese (Brazilian), Russian, English, Spanish
Offered by
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.
Syllabus - What you will learn from this course
3 hours to complete
Introduction to the Data and Machine Learning on Google Cloud Platform Specialization .
Welcome to the Big Data and Machine Learning fundamentals on GCP course. Here you will learn the basics of how the course is structured and the four main big data challenges you will solve for.
3 hours to complete
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 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 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
In this module you will have an existing Apache SparkML recommendation model that is running on-premise. You will learn about recommendation models and how you can run them in the cloud with Cloud Dataproc and Cloud SQL.
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
In this module, you will learn the foundations of BigQuery and big data analysis at scale. You will then learn how to build your own custom machine learning model to predict visitor purchases using just SQL with 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
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
2 hours to complete
Create Streaming Data Pipelines with Cloud Pub/sub and Cloud Dataflow
In this module you will engineer and build an auto-scaling streaming data pipeline to ingest, process, and visualize data on a dashboard. Before you build your pipeline you'll learn the foundations of message-oriented architecture and pitfalls to avoid when designing and implementing modern data pipelines.
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
Classify Images with Pre-Built Models using Vision API and Cloud AutoML
Don't want to create a custom ML model from scratch? Learn how to leverage and extend pre-built ML models like the Vision API and Cloud AutoML for image classification.
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
In this final module, we will review the key challenges, solutions, and topics covered as part of this fundamentals course. We will also review additional resources and the steps you can take to get certified as a Google Cloud Data Engineer.
5 minutes to complete
1 video (Total 5 min)
1 video
Reviews
TOP REVIEWS FROM GOOGLE CLOUD PLATFORM BIG DATA AND MACHINE LEARNING FUNDAMENTALS
by VSMar 2, 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 ADSep 23, 2019
This course really helped me in understanding exactly 'How the Big data and Machine learning can be used in Cloud' and 'The ease to use it'. Thank you for summing all the fundamentals in this course.
by MMNov 13, 2019
In general - great course with a good introduction to GCP tools and platform. Some of the materials might need to get updated though as it seems they are a bit behind the new version of the platform.
by BCJun 9, 2020
Great Course...I knew nothing about cloud computing, but it is easy to see why this has become so popular. I am fascinated by how well GCP integrates so many services in one easy to manage platform.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, 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.
Are there prerequisites for this course?
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
Am I eligible for the Google Cloud Platform free trial?
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/
What if I have already used up my Google Cloud Platform free trial?
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.
How does the free trial work?
View this page for more details: https://cloud.google.com/free-trial/docs/
Is this course similar to CPB100?
Yes, this online course is based on the instructor-led training formerly known as CPB100.
Does this course relate to the Google Certified Professional Data Engineer certification?
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/
What is a Google certification?
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/
Will I earn university credit for completing the Course?
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.
More questions? Visit the Learner Help Center.
