We are happy to advise you!
1­-855­-778­-7246    Contact

Google Cloud Fundamentals: Big Data and Machine Learning (GCF-BDM)

 

Course Overview

This 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.

Course Content

  • Module 1: Big Data and Machine Learning on Google Cloud
  • Module 2: Data Engineering for Streaming Data
  • Module 3: Big Data with BigQuery
  • Module 4: Machine Learning Options on Google Cloud
  • Module 5: The Machine Learning Workflow with Vertex AI
  • Module 6: Course Summary

Who should attend

This class is intended for the following:

  • 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

Certifications

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

Course Objectives

This course teaches participants the following skills:

  • 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.

Outline: Google Cloud Fundamentals: Big Data and Machine Learning (GCF-BDM)

Module 1: Big Data and Machine Learning on Google Cloud
  • Identify the different aspects of Google Cloud’s infrastructure.
  • Identify the big data and machine learning products on Google Cloud.
  • Lab: Exploring a BigQuery Public Dataset
Module 2: Data Engineering for Streaming Data
  • Describe an end-to-end streaming data workflow from ingestion to data visualization.
  • Identify modern data pipeline challenges and how to solve them at scale with Dataflow.
  • Build collaborative real-time dashboards with data visualization tools.
  • Lab: Creating a Streaming Data Pipeline for a Real-Time Dashboard with Dataflow
Module 3: Big Data with BigQuery
  • Describe the essentials of BigQuery as a data warehouse.
  • Explain how BigQuery processes queries and stores data.
  • Define BigQuery ML project phases.
  • Build a custom machine learning model with BigQuery ML.
  • Lab: Predicting Visitor Purchases Using BigQuery ML
Module 4: Machine Learning Options on Google Cloud
  • Identify different options to build ML models on Google Cloud.
  • Define Vertex AI and its major features and benefits.
  • Describe AI solutions in both horizontal and vertical markets.
Module 5: The Machine Learning Workflow with Vertex AI
  • Describe a ML workflow and the key steps.
  • Identify the tools and products to support each stage.
  • Build an end-to-end ML workflow using AutoML.
  • Lab: Vertex AI: Predicting Loan Risk with AutoML
Module 5: Course Summary

This section reviews the topics covered in the course and provides additional resources for further learning.

Describe the data-to-AI lifecycle on Google Cloud and identify the major products of big data and machine learning.

Online Training

Duration 1 day

Price
  • Free offering
Classroom Training

Duration 1 day

Price
  • Canada: CAD 785
 
Click on town name or "Online Training" to book Schedule
This is an Instructor-Led Classroom course
Guaranteed date:   Fast Lane will carry out all guaranteed training regardless of the number of attendees, exempt from force majeure or other unexpected events, like e.g. accidents or illness of the trainer, which prevent the course from being conducted.
Instructor-led Online Training:   This computer icon in the schedule indicates that this date/time will be conducted as Instructor-Led Online Training.
This is a FLEX course, which is delivered both virtually and in the classroom.
United States
Guaranteed to Run Online Training 09:00 US/Central Enroll
Guaranteed to Run Online Training 09:00 US/Central Enroll
Canada
Guaranteed to Run Online Training 09:00 Canada/Central Enroll
Guaranteed to Run Online Training 09:00 Canada/Central Enroll