Course Overview
We conduct Azure IoT training program based on the latest industry standards and cloud architecture practices. Professionals will train you about hardware-cloud integration, protocol mastery, and data analytics to equip you with the functional knowledge and business insights to manage and deploy IoT solutions effectively.
Our training program will fully prepare you to pass your certification exam and also give you an in-depth knowledge about the various and best Azure IoT best practices.
Benefits of Certification
At the end of this course, you will:
- Hardware-Cloud Integration: Participate in mandatory practical labs focused on connecting physical Raspberry Pi and Sense HAT data to cloud ingestion endpoints.
- Instruction from Azure IoT Experts: Learn from certified professionals who actively deploy IoT Hub, Stream Analytics, and Time Series Insights for enterprise clients.
- 50+ Hours of Practical Labs: Engage in extensive scenario-based work covering device setup, protocol implementation, cloud configuration, and troubleshooting.
- Comprehensive Protocol Mastery: Receive in-depth training on MQTT and its security model to achieve efficient, low-power communication between devices.
- Extensive Practice Resources: Access over 1,200 complex, scenario-based questions and 10+ mock exams to build endurance for the final assessment.
- Constant Expert Support: Get immediate, authoritative help on difficult challenges regarding connectivity and Azure integration from certified specialists 24/7.
Module 1: IoT Foundation and Edge Setup
Lesson 1: Core IoT architecture (Device-Gateway-Cloud) and enterprise ROI analysis.
Lesson 2: Hands-on Raspberry Pi OS setup, networking, and Python coding for sensors.
Lesson 3: Developing applications for data cleaning and formatting for reliable ingestion.
Module 2: Communication and Azure Ingestion
Lesson 1: Deep dive into MQTT (QoS, Publish/Subscribe) and overviews of AMQP/HTTP.
Lesson 2: Master the creation and secure configuration of Azure IoT Hub and device identities.
Lesson 3: Practical session connecting the Pi client to the cloud via MQTT for telemetry.
Module 3: Cloud Processing and Data Analytics
Lesson 1: Master Device Twins and Direct Methods for remote control and configuration.
Lesson 2: Use Azure Stream Analytics for defined queries and real-time threshold alerting.
Lesson 3: Design architectures for long-term data persistence and functional dashboards.
Module 4: Advanced Connectivity and Security
Lesson 1: Master SAS tokens and X.509 certificate authentication for secure provisioning.
Lesson 2: Use Azure IoT Hub Diagnostics to troubleshoot disconnection, throttling, and latency.
Lesson 3: Implement security best practices and over-the-air (OTA) updates.
Module 5: Scaling and Future Directions
Lesson 1: Understand IoT Hub partitioning for massive scale and designing for high availability.
Lesson 2: Conceptual overview of Azure IoT Edge and reducing latency through edge processing.
Lesson 3: Knowledge consolidation, final project review, and guidance on advanced certifications.