This course introduces participants to the big data capabilities of Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants get an overview of Google Cloud and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud.
About this Course
Learner Career Outcomes
41%
39%
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
Learner Career Outcomes
41%
39%
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
Introduction to the Data and Machine Learning on Google Cloud Course
Welcome to the Big Data and Machine Learning fundamentals on Google Cloud course. Here you will learn the basics of how the course is structured and the four main big data challenges you will solve for.
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.
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.
Real-time IoT Dashboards with Pub/Sub, Dataflow, and Data Studio
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.
Deriving Insights from Unstructured Data using Machine Learning
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.
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.
Reviews
TOP REVIEWS FROM GOOGLE CLOUD PLATFORM BIG DATA AND MACHINE LEARNING FUNDAMENTALS
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.
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.
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.
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.
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