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Master'sElectronics, Embedded Systems & Telecom Applications open

Master’s in End-to-End IoT Platforms Engineering

Online master's programme of 1,900 hours in end-to-end IoT platforms engineering, structured in 12 modules covering IoT solution architecture, connected device design, connectivity, messaging protocols, cloud platforms, edge processing, IoT data, fleet lifecycle management and end-to-end security, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Design end-to-end IoT architectures with cost and scalability criteria.

02

Develop connected devices with secure firmware.

03

Select the right connectivity technology for each product.

04

Implement cloud IoT platforms and edge processing.

05

Manage the lifecycle of device fleets.

06

Apply security measures that comply with European regulations.

07

Develop a complete IoT solution from device to application.

Profile

Who it's for

  • IoT solutions architects responsible for the full device-to-cloud chain.
  • IoT platform engineers working with AWS, Azure or open-source platforms.
  • Connected firmware developers who want to understand the cloud side.
  • IoT data engineers building telemetry pipelines.
  • IoT security engineers preparing products for European cybersecurity requirements.
  • Connected product managers who need solid technical judgement.
  • Engineering or science graduates aiming to work in consumer electronics.
Standards & tools

What you'll work with

  • ISO/IEC 30141 (IoT reference architecture)
  • ETSI EN 303 645 (cybersecurity for consumer IoT)
  • OASIS MQTT 5.0 (MQTT messaging protocol)
  • IETF RFC 7252 (Constrained Application Protocol, CoAP)
  • OMA LwM2M (lightweight IoT device management)
  • Regulation (EU) 2024/2847 (Cyber Resilience Act)
  • Regulation (EU) 2016/679 (General Data Protection Regulation, GDPR)
  • NIST IR 8259A (IoT device cybersecurity capability core baseline)
  • AWS IoT Core
  • Azure IoT Hub
  • ThingsBoard
  • Eclipse Mosquitto
  • Apache Kafka
Syllabus

12 modules · 1900 h

  1. 1.1Device, connectivity, platform and application layers
  2. 1.2Functional and non-functional requirements
  3. 1.3Reference IoT architecture patterns
  4. 1.4Cloud, edge and hybrid deployment models
  5. 1.5Total cost of ownership
  6. 1.6Connected product lifecycle
  7. 1.7ISO/IEC 30141 reference architecture
  8. 1.8Documentation with the C4 model
  9. 1.9Choice of suppliers and dependencies
  10. 1.10Case study: architecture of a connected consumer product
  1. 2.1Selection of microcontroller and wireless SoC
  2. 2.2Sensors, actuators and interfaces
  3. 2.3PCB design and radio certification
  4. 2.4Device power management
  5. 2.5Real-time embedded operating systems
  6. 2.6Embedded Linux with Yocto
  7. 2.7Secure boot and root of trust
  8. 2.8Factory provisioning
  9. 2.9Design for manufacturing and testing
  10. 2.10Practical: prototype with ESP32 and environmental sensors
  1. 3.1Wi-Fi, Bluetooth LE and Thread
  2. 3.2Matter for the connected home
  3. 3.3LTE-M and NB-IoT cellular networks
  4. 3.4Public and private LoRaWAN networks
  5. 3.5Low-throughput satellite connectivity
  6. 3.6SIM and eSIM management
  7. 3.7Connectivity selection by cost and consumption
  8. 3.8Intermittent connectivity and local storage
  9. 3.9Roaming and operator agreements
  10. 3.10Lab: power consumption comparison between BLE and Wi-Fi
  1. 4.1MQTT 5 and its new features
  2. 4.2CoAP and resource observation
  3. 4.3HTTP and WebSockets on devices
  4. 4.4AMQP for enterprise integration
  5. 4.5JSON, CBOR and Protocol Buffers formats
  6. 4.6Topic and schema design
  7. 4.7Quality of service and guaranteed delivery
  8. 4.8Payload compression and efficiency
  9. 4.9Comparison of MQTT brokers
  10. 4.10Workshop: designing the topic space for a fleet
  1. 5.1AWS IoT Core and associated services
  2. 5.2Azure IoT Hub and DPS
  3. 5.3ThingsBoard and Eclipse open platforms
  4. 5.4Device registry and identity
  5. 5.5Device shadows and twins
  6. 5.6Rules engines and routing
  7. 5.7Integration with serverless services
  8. 5.8Multi-tenancy in IoT platforms
  9. 5.9Vendor lock-in and portability
  10. 5.10Practical: connecting a fleet to AWS IoT Core
  1. 6.1Gateways and edge nodes
  2. 6.2Containers on edge devices
  3. 6.3AWS Greengrass and Azure IoT Edge
  4. 6.4Model inference at the edge
  5. 6.5Local filtering and aggregation
  6. 6.6Disconnected operation and later synchronisation
  7. 6.7Workload orchestration at the edge
  8. 6.8Updating edge applications
  9. 6.9Hardware resources and limitations
  10. 6.10Lab: TinyML inference on an edge node
  1. 7.1Large-scale data ingestion
  2. 7.2Time-series telemetry storage
  3. 7.3Data lakes and columnar formats
  4. 7.4Stream processing
  5. 7.5Sensor data quality and cleansing
  6. 7.6Retention and storage costs
  7. 7.7Descriptive analytics and dashboards
  8. 7.8Machine learning on IoT data
  9. 7.9Data access APIs
  10. 7.10Practical: streaming pipeline with Kafka
  1. 8.1Secure onboarding and provisioning
  2. 8.2Remote parameter configuration
  3. 8.3Over-the-air firmware updates
  4. 8.4Fleet health monitoring
  5. 8.5Remote diagnostics and event logging
  6. 8.6Decommissioning and end of life
  7. 8.7LwM2M management protocol
  8. 8.8Rollback and staged rollouts
  9. 8.9Fleet reliability indicators
  10. 8.10Case study: OTA strategy for 50,000 devices
  1. 9.1Threat modelling in IoT
  2. 9.2Identity with X.509 certificates
  3. 9.3Secure elements and TPM
  4. 9.4Encryption in transit and at rest
  5. 9.5Cloud platform security
  6. 9.6Vulnerability management and SBOM
  7. 9.7European Cyber Resilience Act
  8. 9.8Penetration testing of devices
  9. 9.9Incident response in fleets
  10. 9.10Workshop: STRIDE threat model of a product
  1. 10.1Mobile apps for devices
  2. 10.2Web dashboards for operators
  3. 10.3Notifications and alerts
  4. 10.4Integration with voice assistants
  5. 10.5BLE provisioning interfaces
  6. 10.6Accessibility and usability
  7. 10.7Third-party APIs
  8. 10.8Product usage analytics
  9. 10.9Subscription and service models
  10. 10.10Practical: device onboarding app
  1. 11.1Load testing with simulated devices
  2. 11.2Platform observability
  3. 11.3High availability and recovery
  4. 11.4Cloud cost optimisation
  5. 11.5Infrastructure as code
  6. 11.6Continuous integration and delivery
  7. 11.7Service level agreements
  8. 11.8Compliance and data protection
  9. 11.924×7 support and operations
  10. 11.10Case study: simulating one million messages per minute
  1. 12.1Definition of the connected product
  2. 12.2End-to-end architecture
  3. 12.3Device design and prototype
  4. 12.4Platform implementation
  5. 12.5Security and fleet management
  6. 12.6Scalability testing
  7. 12.7Cost and feasibility analysis
  8. 12.8Conclusions on the IoT solution
  9. 12.9Master's Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: you progress at your own pace within each intake, so the programme fits around your job.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is AWS IoT Core, Azure IoT Hub, ThingsBoard, Eclipse Mosquitto and Apache Kafka, in free, academic or evaluation versions. Testing is studied through real procedures: connecting and managing device fleets on cloud platforms, deploying over-the-air firmware updates, and load testing with simulated devices. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: ISO/IEC 30141, ETSI EN 303 645, OASIS MQTT 5.0, IETF RFC 7252, OMA LwM2M, Regulation (EU) 2024/2847, Regulation (EU) 2016/679, NIST IR 8259A.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of ISO/IEC 30141, ETSI EN 303 645 and OASIS MQTT 5.0 applied to real cases, not as a theoretical annex.
Industry software:AWS IoT Core, Azure IoT Hub, ThingsBoard, Eclipse Mosquitto and Apache Kafka, in free, academic or evaluation versions.
Master's Thesis with defence:A complete connected product, from device prototype to cloud platform, security, fleet management and scalability testing, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Product and architecture
Define the connected product and design its end-to-end architecture.
Device prototype
Design and build the device prototype with secure firmware.
Platform implementation
Implement the cloud platform, messaging and data pipeline.
Security and scalability
Apply fleet management and security measures and run scalability tests.
Master's Thesis
Analyse costs and feasibility and present the complete solution, defended before a panel.
Career opportunities

Where this takes you

IoT Solutions ArchitectIoT Platform EngineerConnected Firmware DeveloperIoT Data EngineerIoT Security EngineerConnected Product Manager
Admissions & scholarships

Requirements

  • A university degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • An internet connection and a computer capable of running the programme's software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with AWS IoT Core, Azure IoT Hub, ThingsBoard, Eclipse Mosquitto and Apache Kafka, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.

A university degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the programme's software, and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

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