Dimitris Kyrtopoulos | dk

Google Cloud Big Data and Machine Learning Fundamentals

Google Cloud Big Data and Machine Learning Fundamentals Dimitris Kyrtopoulos



About this Course

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.

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

Google Cloud Platform
Cloud Computing


Week 1: Introduction to the Google Cloud Big Data and Machine Learning Fundamentals Course
Welcome to the Google Cloud Big Data and Machine Learning Fundamentals 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 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.

Week 2: 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.

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.