Course
Skills
Google Cloud Big Data and Machine Learning Fundamentals
This course introduces participants to the big data capabilities of Google Cloud.
What you'll learn
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.
Table of contents
Introduction to the Google Cloud Big Data and Machine Learning Fundamentals Course
76mins
- Welcome to Google Cloud Big Data and Machine Learning Fundamentals 6m
- Introduction to Google Cloud 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
- Google Cloud Public Datasets program 0m
- Lab: Exploring a BigQuery Public Dataset 0m
- Choosing the right approach 6m
- What you can do with Google Cloud 4m
- Activity: Explore real customer solution architectures 7m
- Key roles in a data-driven organization 7m
- Module Resources 0m
Recommending Products Using Cloud SQL and Spark
51mins
- How businesses use recommendation systems 7m
- Introduction to machine learning 6m
- Challenge: ML for recommending housing rentals 9m
- Approach: Move from on-premise to Google Cloud 10m
- Demo: From zero to an Apache Spark job in 10 minutes or less 6m
- Challenge: Utilizing and tuning on-premise clusters 6m
- Move storage off-cluster with Google Cloud Storage 5m
- Lab Intro: Recommending Products Using Cloud SQL and Spark 2m
- Lab: Recommending Products Using Cloud SQL and Spark 0m
- Module Resources 0m
Predict Visitor Purchases Using BigQuery ML
74mins
- Introduction to BigQuery 6m
- Demo: Query 2 billion lines of Github 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
- BigQuery ML: Create models with SQL 4m
- Phases in ML model lifecycle 3m
- BigQuery ML: key features walkthrough 5m
- Lab Intro: Predicting Visitor Purchases with a Classification Model with BigQuery ML 0m
- Lab: Predicting Visitor Purchases with a Classification Model with BigQuery ML 0m
- Module Resources 0m
Real-time IoT Dashboards with Pub/Sub, Dataflow, and Data Studio
30mins
- Modern data pipeline challenges 3m
- Message-oriented architectures with Pub/Sub 6m
- Designing streaming pipelines with Apache Beam 4m
- Implementing streaming pipelines on Dataflow 3m
- Visualizing insights with Data Studio 3m
- Creating charts with Data Studio 3m
- Data Studio walkthrough 7m
- Lab Intro: Creating a Streaming Data Pipeline for a Real-Time Dashboard with Dataflow 1m
- Lab: Creating a Streaming Data Pipeline for a Real-Time Dashboard with Dataflow 0m
- Module Resources 0m
Deriving Insights from Unstructured Data Using Machine Learning
54mins
- 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 Intro: Classifying Images of Clouds in the Cloud with AutoML Vision 0m
- Lab: Classifying Images of Clouds in the Cloud with AutoML Vision 0m
- Building a Custom Model 1m
- Demo: Text classification done three ways 22m
- Additional resources to build custom models 0m
- Module Resources 0m
Summary
5mins
Course Resource
0mins
