Google Cloud Platform Big Data and Machine Learning Fundamentals

سرفصل های دوره

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

1. Introduction to the Data and Machine Learning on Google Cloud Course

1. Course Overview

2. Course Introduction

2. Introduction to Google Cloud Platform

01. Introduction to Google Cloud Platform

02. Introduction to Google Cloud Platform

03. Compute Power for Analytic and ML Workloads

04. Demo - Creating a VM on Compute Engine

05. Elastic Storage with Google Cloud Storage

06. Build on Googles Global Network

07. Security - On-premise vs Cloud-native

08. Evolution of Google Cloud Big Data Tools

09. Getting Started With GCP And Qwiklabs

10. Lab- Exploring a BigQuery Public Dataset

11. Choosing the Right Approach

12. What you can do with GCP

13. Activity - Explore a Customer Use Case

14. The Different Data Roles in an Organization

3. Recommending Products using Cloud SQL and Spark

01. Product Recommendations using Cloud SQL and Spark

02. How Businesses Use Recommendation Systems

03. Introduction to Machine Learning

04. ML for Recommending Housing Rentals

05. Move From On-Premise to Google Cloud Platform

06. Demo - From Zero to an Apache Spark Job in 10 Minutes or Less

07. Challenge- Utilizing and tuning on-premise clusters

08. Move storage off-cluster with Google Cloud Storage

09. Lab - Recommending Products Using Cloud SQL and Spark

10. Lab- Recommending Products Using Cloud SQL and Spark

4. Predict Visitor Purchases Using BigQuery ML

01. Predicting Visitor Purchases with Classification using BigQuery ML

02. Introduction to BigQuery

03. Demo - Query 2 Billion Lines of Code in Less Than 30 Seconds

04. BigQuery - Fast SQL Engine

05. Demo - Exploring Bike Share Data with SQL

06. Data Quality

07. BigQuery Managed Storage

08. Insights from Geographic Data

09. Demo - Analyzing Lightning Strikes with BigQuery GIS

10. Choosing a ML Model Type for Structured Data

11. Predicting Customer Lifetime Value

12. BigQueryML - Create Models with SQL

13. Phases in ML Model Lifecycle

14. BigQuery ML - Key Features Walkthrough

15. Lab- Predicting Visitor Purchases with a Classification Model with BigQuery ML

5. Real-time IoT Dashboards with Pub-Sub, Dataflow, and Data Studio

01. Real-time Dashboards with Pub_Sub, Dataflow, and Data Studio

02. Modern Data Pipeline Challenges

03. Message-oriented Architectures with Cloud Pub-Sub

04. Designing Streaming Pipelines with Apache Beam

05. Implementing Streaming Pipelines on Cloud Dataflow

06. Visualizing Insights with Data Studio

07. Creating Charts with Data Studio

08. Demo - Data Studio Walkthrough

09. Lab - Creating a Streaming Data Pipeline for a Real-Time Dashboard with Dataflow

10. Lab- Creating a Streaming Data Pipeline for a Real-Time Dashboard with Dataflow

6. Deriving Insights from Unstructured Data using Machine Learning

01. Deriving Insights from Unstructured Data using Machine Learning

02. Where is Unstructured ML used in business-

03. How Does ML on Unstructured Data Work-

04. Demo - ML built into Google Photos

05. Comparing Approaches to ML

06. Demo - Using ML Building Blocks

07. Using Pre-built AI to Create a Chatbot

08. Customizing Pre-built Models with AutoML

09. Lab - Classifying Images of Clouds in the Cloud with AutoML Vision

10. Lab- Classifying Images of Clouds in the Cloud with AutoML Vision

11. Building a Custom Model

12. Demo - Text Classification Done Three Ways

7. Summary

1. Summary

2. Course Summary

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تولید کننده: PluralSight