Overview

This GCPBD: Google Cloud Big Data and Machine Learning Fundamentals course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

 

Skills Covered

  • Recognize the data-to-AI lifecycle on Google Cloud and the major products of big data and machine learning.
  • Design streaming pipelines with Dataflow and Pub/Sub.
  • Analyze big data at scale with BigQuery.
  • Identify different options to build machine learning solutions on Google Cloud.
  • Describe a machine learning workflow and the key steps with Vertex AI.
  • Build a machine learning pipeline using AutoML.

Who Should Attend

  • Data analysts, data scientists, and business analysts who are getting started with Google Cloud
  • Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results, and creating reports
  • Executives and IT decision makers evaluating Google Cloud for use by data scientists

Course Curriculum

Prerequisites

Basic understanding of one or more of the following:

  • Database query language such as SQL
  • Data engineering workflow from extract, transform, load, to analysis, modeling, and deployment
  • Machine learning models such as supervised versus unsupervised models

Download Syllabus