Google Cloud IoT syllabus

Introduction to IoT

• Understanding IoT Concepts and Applications
• Overview of IoT Architecture
• IoT Devices and Sensors

Google Cloud Platform (GCP) Fundamentals

• Introduction to Google Cloud Platform
• GCP Services Relevant to IoT (Compute Engine, Pub/Sub, Dataflow, BigQuery, etc.)
• Setting Up a GCP Account and Project

Google Cloud IoT Core

• Overview of Google Cloud IoT Core
• Device Registration and Management
• Communication Protocols (MQTT, HTTP)
• Security Best Practices

Device Connectivity

• Configuring Devices to Connect to Google Cloud IoT Core
• Choosing Appropriate Communication Protocols
• Device Authentication and Authorization

Data Processing and Analytics

• Data Ingestion with Cloud Pub/Sub
• Real-Time Data Processing with Cloud Dataflow
• Storing IoT Data in BigQuery
• Analyzing IoT Data with Data Studio and Other Visualization Tools

Edge Computing and IoT Edge

• Overview of Edge Computing
• Google Cloud IoT Edge Features and Capabilities
• Implementing Edge Computing Solutions with IoT Edge

Machine Learning and AI at the Edge

• Introduction to Machine Learning and AI
• Integrating Machine Learning Models with IoT Devices
• Edge AI Applications and Use Cases

IoT Security and Compliance

• Security Considerations for IoT Deployments
• Implementing End-to-End Security in IoT Solutions
• Compliance Standards and Regulations (GDPR, HIPAA, etc.)

IoT Solution Deployment and Management

• Deploying IoT Solutions on Google Cloud Platform
• Monitoring and Managing IoT Devices and Infrastructure
• Scaling IoT Deployments for Large-Scale Applications

Advanced IoT Architectures

• High Availability and Fault Tolerance in IoT Systems
• Scalable IoT Architectures for Large-Scale Deployments
• Hybrid Cloud and Edge Computing Architectures
• Multi-Cloud IoT Solutions and Interoperability

Advanced Device Management

• Dynamic Device Provisioning and Onboarding
• Fleet Management and Over-the-Air Updates (OTA)
• Device State Management and Synchronization
• Advanced Device Monitoring and Diagnostics

Advanced Data Processing and Analytics

• Complex Event Processing (CEP) for Real-Time Analytics
• Advanced Data Transformations and Enrichment
• Predictive Analytics and Machine Learning at Scale
• Optimization Techniques for Data Storage and Querying

Advanced Security Practices

• Zero-Trust Security Architectures for IoT
• Identity and Access Management (IAM) for IoT Devices
• Advanced Encryption and Key Management Techniques
• Security Monitoring and Threat Detection for IoT Deployments

Edge Computing Optimization

• Optimizing Edge Computing Resources for Performance and Efficiency
• Edge Caching and Local Data Processing Techniques
• Latency Optimization Strategies for Real-Time Applications
• Edge-to-Cloud Synchronization and Data Consistency

Advanced Machine Learning Integration

• Advanced ML Model Deployment Strategies for Edge Devices
• Transfer Learning and Federated Learning for IoT
• Edge AI Model Optimization and Compression Techniques
• Edge-Based Anomaly Detection and Predictive Maintenance

Compliance and Regulatory Considerations

• Advanced Compliance Frameworks and Regulations (e.g., ISO 27001, NIST)
• Privacy-Preserving Techniques for IoT Data
• Data Residency and Sovereignty Requirements
• Compliance Auditing and Reporting for IoT Deployments

Advanced IoT Solution Deployment

• Infrastructure as Code (IaC) for IoT Deployments
• CI/CD Pipelines for Continuous Integration and Deployment
• Advanced Monitoring, Logging, and Debugging Techniques
• Performance Optimization and Cost Management Strategies