Google Cloud Fundamentals: Big Data & Machine Learning

Name: Google Cloud Fundamentals: Big Data & Machine Learning
Start: 2024-04-08 00:00:00
Location: Virtual Classroom

Looking to master Google Cloud’s big data and machine learning capabilities? Delve into the process, challenges and benefits of building big data pipelines and ML models with Vertex AI on this one-day course.

1 day course

Partner of the Year

Virtual, Private

Virtual Classroom

A convenient and interactive learning experience, that enables you to attend one of our courses from the comfort of your own home or anywhere you can log on. We offer Virtual Classroom on selected live classroom courses where this will appear as an option under the location drop down if available. These can also be booked as Private Virtual Classrooms for exclusive business sessions.

Private

A private training session for your team. Groups can be of any size, at a location of your choice including our training centres.

As an award-winning Google Cloud Partner, we’ve been selected to run this Big Data & Machine Learning Fundamentals course.

Our instructors are industry experts who work with Google Cloud on a daily basis. Through virtual classes and practical labs, they will help you navigate key big data and machine learning processes and show you the role different services play in supporting the data-to-AI lifecycle.

Topics covered include BigQuery, Dataflow, Pub / Sub, Apache Beam, Looker, Data Studio, Document AI, Contact Center AI (CCAI) and Kubernetes Engine, among others.

Our Google Cloud Fundamentals: Big Data & Machine Learning course is delivered via Virtual Classroom. We also offer it as a private training session that can be delivered virtually or at a location of your choice in South Africa.

Course overview

Who should attend:

This course is suitable for:

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

What you'll learn:

By the end of this course, you will be able to:

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

Prerequisites

To get the most out of this course, you should have basic understanding of one or more of the following:

A database query language such as SQL
Aspects of the data engineering workflow – from extract, transform and load, to analysis, modeling, and deployment
Machine learning models, such as supervised versus unsupervised models

Course agenda

Module 1: Course Introduction

Recognize the data-to-AI lifecycle on Google Cloud
Identify the connection between data engineering and machine learning

Module 2: Big Data & 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 3: 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
Quiz

Module 4: Big Data with Big Query

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 5: 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 6: 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

Upcoming courses

Virtual Classroom Google Cloud Fundamentals: Big Data & Machine Learning	Mon, Apr 08 2024 R6,000 ex VAT	ADD TO BASKET
Virtual Classroom Google Cloud Fundamentals: Big Data & Machine Learning	Mon, Aug 05 2024 R6,000 ex VAT	ADD TO BASKET
Virtual Classroom Google Cloud Fundamentals: Big Data & Machine Learning	Mon, Dec 02 2024 R6,000 ex VAT	ADD TO BASKET

Upcoming courses

Virtual Classroom

Google Cloud Fundamentals: Big Data & Machine Learning

Mon, Apr 08 2024

R6,000 ex VAT

ADD TO BASKET

Virtual Classroom

Google Cloud Fundamentals: Big Data & Machine Learning

Mon, Aug 05 2024

R6,000 ex VAT

ADD TO BASKET

Virtual Classroom

Google Cloud Fundamentals: Big Data & Machine Learning

Mon, Dec 02 2024

R6,000 ex VAT

ADD TO BASKET

Book this course

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R6,000 ex VAT