Data Engineering
Google Cloud Fundamentals: Big Data & Machine Learning
Unlock the full potential of Google Cloud’s big data and machine learning capabilities in this one-day intensive course. Learn the process, overcome challenges, and reap the benefits of building robust big data pipelines and deploying ML models using Vertex AI
Duration
1 Days
What you'll learn
Data-to-AI Workflow:
Understand Google Cloud’s data-to-AI lifecycle and key tools.
Big Data & Streaming:
Design streaming pipelines and analyze datasets with BigQuery.
ML Solutions & Pipelines:
Build machine learning workflows with Vertex AI and AutoML.
COURSE AGENDA
Course Introduction
- Recognize the data-to-AI lifecycle on Google Cloud.
- Understand the connection between data engineering and machine learning workflows.
Big Data & Machine Learning on Google Cloud
- Explore the components of Google Cloud’s infrastructure.
- Identify Google Cloud’s big data and machine learning products.
- Lab: Analyze a BigQuery public dataset to gain hands-on experience.
Data Engineering for Streaming Data
- Describe an end-to-end streaming workflow from data ingestion to visualization.
- Address challenges in modern data pipelines using Dataflow.
- Build collaborative real-time dashboards with visualization tools.
- Lab: Create a streaming data pipeline for a real-time dashboard using Dataflow.
- Quiz: Test your knowledge on streaming data workflows.
Big Data with BigQuery
- Understand the essentials of BigQuery as a powerful data warehouse.
- Learn how BigQuery processes queries and stores data efficiently.
- Define the phases of a BigQuery ML project.
- Build a custom machine learning model using BigQuery ML.
- Lab: Predict visitor purchases with BigQuery ML.
Machine Learning Options on Google Cloud
- Identify the various ML modeling options available on Google Cloud.
- Explore the features and benefits of Vertex AI.
- Understand AI solutions for horizontal and vertical markets.
The Machine Learning Workflow with Vertex AI
- Describe the key steps of an ML workflow using Vertex AI.
- Identify the tools and products that support each stage of the workflow.
- Build an end-to-end ML workflow with AutoML.
- Lab: Predict loan risk using Vertex AI and AutoML.
Comprehensive Review
Consolidate Learning:
Review key Google Cloud concepts for a solid foundation.
Connect Concepts:
Understand how modules apply to real-world scenarios.
Prepare for Implementation:
Apply course knowledge to practical Google Cloud solutions.
Cloud Functions Core
- Deploy serverless solutions
- Implement function triggers
- Secure function access
Advanced Functions
- Integrate with databases
- Manage secrets and variables
- Implement best practices
Workflow Automation
- Design serverless workflows
- Implement logic controls
- Master service authentication
- Build automated processes