Google Cloud Big Data and Machine Learning Fundamentals

Course Certification

This course helps you prepare to take the:
Google Cloud Certified Professional Data Engineer Exam;

Course Outline

Module 1: Introducing Google Cloud Platform

• Google Platform Fundamentals Overview.
• Google Cloud Platform Big Data Products.
• Lab: Sign up for Google Cloud Platform.

Module 2: Compute and Storage Fundamentals

• CPUs on demand (Compute Engine).
• A global file system (Cloud Storage).
• Cloud Shell.
• Lab: Set up an Ingest-Transform-Publish data processing pipeline.

Module 3: Data Analytics on the Cloud

• Stepping stones to the cloud.
• Cloud SQL: your SQL database on the cloud.
• Lab: Importing data into CloudSQL and running queries.
• Spark on Dataproc.
• Lab: Machine Learning Recommendations with Spark on Dataproc.

Module 4: Scaling Data Analysis

• Fast random access.
• Computer Lab.
• BigQuery.
• Lab: Build a Machine Learning Dataset.

Module 5: Machine Learning

• Machine Learning with TensorFlow.
• Lab: Carry out ML with TensorFlow.
• Pre-built models for common needs.
• Lab: Employ ML APIs.

Module 6: Data Processing Architectures

• Message-oriented architectures with Pub/Sub.
• Creating pipelines with Dataflow.
• Reference architecture for real-time and batch data processing.

Module 7: Summary

• Why GCP?.
• Where to go from here.
• Additional Resources

Course Mode

Instructor-Led Remote Live Classroom Training;

Trainers

Trainers are GCP Official Instructors and certified in other IT technologies, with years of hands-on experience in the industry and in Training.

Lab Topology

For all types of delivery, the Trainee can access real Cisco equipment and systems in our laboratories or directly at the Cisco data centers remotely 24 hours a day. Each participant has access to implement the various configurations thus having a practical and immediate feedback of the theoretical concepts.
Here are some Labs topologies available: