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This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants get an overview of the Google Cloud platform 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 Platform.

Target Audience

Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform.
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 Platform for use by data scientists.

To get the most of out of this course, participants should have:

Basic proficiency with common query language such as SQL.
Experience with data modeling, extract, transform, load activities.
Developing applications using a common programming language such Python.
Familiarity with machine learning and/or statistics.

Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.
Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.
Employ BigQuery and Cloud Datalab to carry out interactive data analysis.
Train and use a neural network using TensorFlow.
Employ ML APIs.
Choose between different data processing products on the Google Cloud Platform.

Session 1

Welcome

Facility Logistics

1 Introduction to Google Cloud Platform

Google Cloud Platform infrastructure and big data products
Demo: BigQuery Github query
The different data roles in an organization
What you can do with GCP
Activity: Explore a customer use case
Lab 1: Exploring a Public Dataset with BigQuery

2 Product Recommendations using Cloud SQL and Spark

Compare Google Cloud Big Data products and services
Managed Hadoop in the cloud
Demo: Creating a Cluster
Your SQL database in the cloud
Lab 2: Product Recommendation using Cloud SQL and Spark

3 Predicting Visitor Purchases using BigQuery Machine Learning

Introduction to BigQuery
Fast SQL Query Engine
Managed Storage for Datasets
Demo: Google Sheets to BQ
Insights from Geographic data
Demo: BigQuery ML
Creating ML models with SQL w/BigQuery ML
Lab 3: Predicting Visitor Purchases BigQuery ML

Session 2

4 Real-time Dashboards with Pub/Sub, Dataflow, and Data Studio

Introduction
Message-oriented architectures
Serverless data pipelines
Data Visualization w/Data Studio
Lab 4: Real-time Dashboards with Pub/Sub, Dataflow, and Data Studio

5 Deriving Insights from Unstructured Data using Machine Learning

Introduction to Machine Learning
Pre-built ML models
Demo: Cloud Vision API
Codeless ML with AutoML
Lab 5: Classify Images using AutoML

6 Summary

Recap of lesson

Upcoming Trainings

Join our public courses in our New Zealand facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom

19 May 2024