Google Cloud Platform Big Data and Machine Learning Fundamentals
This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.
What you'll learn
This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.
Table of contents
Course Overview
10mins
Introduction to Google Cloud Platform
70mins
- Module 1- Introduction to Google Cloud Platform 0m
- Introduction to Google Cloud Platform 4m
- Compute Power for Analytic and ML Workloads 10m
- Demo - Creating a VM on Compute Engine 14m
- Elastic Storage with Google Cloud Storage 7m
- Build on Google's Global Network 3m
- Security - On-premise vs Cloud-native 3m
- Evolution of Google Cloud Big Data Tools 5m
- Lab: Explore a BigQuery Public Dataset 0m
- Choosing the Right Approach 6m
- What you an do with GCP 4m
- Activity - Explore a Customer Use Case 7m
- The Different Data Roles in an Organization 7m
Recommending Products using Cloud SQL and Spark
51mins
- Module 2 - Recommending Products using Cloud SQL and Spark 0m
- How Businesses Use Recommendation Systems 7m
- Introduction to Machine Learning 6m
- ML for Recommending Housing Rentals 9m
- Move From On-Premise to Google Cloud Platform 10m
- Demo - From Zero to an Apache Spark Job in 10 Minutes or Less 6m
- Utilizing and Tuning On-Premise Clusters 6m
- Move Storage Off-Cluster with Google Cloud Storage 5m
- Lab - Recommend Products Using Cloud SQL and SparkML 2m
- Lab: Recommend Products using ML with Cloud SQL and Dataproc 0m
Predict Visitor Purchases Using BigQuery ML
74mins
- Module 3 - Predict Visitor Purchases Using BigQuery ML 0m
- Introduction to BigQuery 6m
- Demo - Query 2 Billion Lines of Code in Less Than 30 Seconds 11m
- BigQuery - Fast SQL Engine 4m
- Demo - Exploring Bike Share Data with SQL 12m
- Data Quality 5m
- BigQuery Managed Storage 5m
- Insights from Geographic Data 2m
- Demo - Analyzing Lightning Strikes with BigQuery GIS 7m
- Choosing a ML Model Type for Structured Data 5m
- Predicting Customer Lifetime Value 5m
- BigQueryML - Create Models with SQL 4m
- Phases in ML Model Lifecycle 3m
- BigQuery ML - Key Features Walkthrough 5m
- Lab: Predict Visitor Purchases with a Classification Model with BigQuery ML 0m
Create Streaming Data Pipelines with Cloud Pub/sub and Cloud Dataflow
30mins
- Module 4 - Create Streaming Data Pipelines with Cloud Pub/sub and Cloud Dataflow 0m
- Modern Data Pipeline Challenges 3m
- Message-oriented Architectures with Cloud Pub/Sub 6m
- Designing Streaming Pipelines with Apache Beam 4m
- Implementing Streaming Pipelines on Cloud Dataflow 3m
- Visualizing Insights with Data Studio 3m
- Creating Charts with Data Studio 3m
- Demo - Data Studio Walkthrough 7m
- Lab - Real-time IoT Dashboards with Pub/Sub, Dataflow, and Data Studio 1m
- Lab: Create a Streaming Data Pipeline for a Real-Time Dashboard with Cloud Dataflow 0m
Classify Images with Pre-Built Models using Vision API and Cloud AutoML
54mins
- Module 5 - Classify Images with Pre-Built Models using Vision API and Cloud AutoML 0m
- Where is Unstructured ML used in business? 4m
- How Does ML on Unstructured Data Work? 3m
- Demo - ML built into Google Photos 2m
- Comparing Approaches to ML 3m
- Demo - Using ML Building Blocks 7m
- Using Pre-built AI to Create a Chatbot 5m
- Customizing Pre-built Models with AutoML 7m
- Lab - Classify Images with Pre-built ML Models 0m
- Lab: Classify Images with Pre-built ML Models using Cloud Vision API and AutoML 0m
- Building a Custom Model 1m
- Demo - Text Classification Done Three Ways 22m
Summary
5mins
