Postgraduate DiplomaElectronics, Embedded Systems & Telecom Applications open

Postgraduate Diploma in Cloud-Edge Architectures for IoT

Online Postgraduate Diploma of 800 hours in Cloud-Edge Architectures for IoT. 8 modules covering ISO/IEC 30141, OASIS MQTT 5.0 and Kubernetes K3s. Assigned tutor and open enrolment.

Duration800 h
ModeOnline
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Analyse reference architectures for IoT systems.

02

Select messaging protocols suited to each case.

03

Deploy containerised applications on edge nodes.

04

Integrate devices with cloud-based IoT platforms.

05

Automate deployment using infrastructure as code and GitOps.

06

Design end-to-end security across the cloud-edge continuum.

07

Evaluate the performance and cost of alternative architectural approaches.

Profile

Who it's for

  • IoT solutions architect who wants to specialise in Cloud-Edge Architectures for IoT.
  • Cloud engineer who wants to specialise in Cloud-Edge Architectures for IoT.
  • Edge computing engineer who wants to specialise in Cloud-Edge Architectures for IoT.
  • DevOps engineer who wants to specialise in Cloud-Edge Architectures for IoT.
  • IoT platform developer who wants to specialise in Cloud-Edge Architectures for IoT.
  • Digital transformation consultant who wants to specialise in Cloud-Edge Architectures for IoT.
  • Engineering or science graduates seeking to enter industry.
Standards & tools

What you'll work with

  • ISO/IEC 30141
  • OASIS MQTT 5.0
  • IEC 62443-3-3
  • ISO/IEC 22123-1
  • ETSI GS MEC 003
  • ETSI EN 303 645
  • Regulation (EU) 2016/679
Syllabus

8 modules · 800 h

  1. 1.1ISO/IEC 30141 reference model
  2. 1.2Device, edge, platform and business layers
  3. 1.3The cloud-edge-device continuum
  4. 1.4Criteria for distributing computing
  5. 1.5Event-driven communication patterns
  6. 1.6Non-functional requirements and quality attributes
  7. 1.7IIRA and RAMI 4.0 architecture
  8. 1.8Cost models and TCO
  9. 1.9Documented architectural decisions
  10. 1.10Case study: selecting an architecture for a use case
  1. 2.1MQTT 5.0: topics, QoS and sessions
  2. 2.2Sparkplug B and device state
  3. 2.3AMQP and message queues
  4. 2.4CoAP and lightweight REST resources
  5. 2.5Messaging brokers and clusters
  6. 2.6Bridges between local and cloud brokers
  7. 2.7Designing topic schemas
  8. 2.8Security at the messaging layer
  9. 2.9Broker load testing
  10. 2.10Laboratory: MQTT cluster with Mosquitto and EMQX
  1. 3.1Industrial gateways and edge hardware
  2. 3.2Containers on resource-constrained devices
  3. 3.3Lightweight Kubernetes: K3s and KubeEdge
  4. 3.4AWS IoT Greengrass and Azure IoT Edge
  5. 3.5Local processing and data filtering
  6. 3.6Offline operation and synchronisation
  7. 3.7AI inference at the edge
  8. 3.8Remote management of edge nodes
  9. 3.9MEC in 5G networks
  10. 3.10Practical: deploying a microservice on K3s
  1. 4.1Managed IoT services on public cloud
  2. 4.2Device registry and device twin
  3. 4.3Rules engines and routing
  4. 4.4Time-series storage
  5. 4.5Serverless processing
  6. 4.6Data lakes and analytics
  7. 4.7Multi-tenancy and isolation
  8. 4.8Service limits and scaling
  9. 4.9Vendor lock-in and portability
  10. 4.10Laboratory: data ingestion on a cloud platform
  1. 5.1Infrastructure as code for IoT
  2. 5.2GitOps across edge fleets
  3. 5.3Declarative deployments with Helm
  4. 5.4Distributed configuration management
  5. 5.5Updating applications at the edge
  6. 5.6Observability of distributed nodes
  7. 5.7Latency-based workload scheduling
  8. 5.8Fault tolerance and recovery
  9. 5.9Version management of AI models
  10. 5.10Workshop: GitOps pipeline with Argo CD
  1. 6.1Device identity and PKI
  2. 6.2Mutual TLS authentication
  3. 6.3Zero trust in IoT architectures
  4. 6.4Secrets management at the edge
  5. 6.5Network segmentation and conduits
  6. 6.6IEC 62443 requirements across the continuum
  7. 6.7Data protection and GDPR
  8. 6.8Centralised audit logging
  9. 6.9Response to node compromise
  10. 6.10Case study: cloud-edge threat model
  1. 7.1Latency and bandwidth modelling
  2. 7.2Load and scalability testing
  3. 7.3Cloud cost optimisation
  4. 7.4Energy consumption at the edge
  5. 7.5Sizing gateways
  6. 7.6Aggregation and sampling strategies
  7. 7.7Availability and service level agreements
  8. 7.8Evaluating architectural alternatives
  9. 7.9Digital sustainability metrics
  10. 7.10Practical: cost analysis of an architecture
  1. 8.1Use case and requirements
  2. 8.2Logical and physical architecture
  3. 8.3Selection of protocols and platforms
  4. 8.4Edge processing design
  5. 8.5Security and deployment plan
  6. 8.6Functional prototype
  7. 8.7Performance and cost testing
  8. 8.8Conclusions and evolution
  9. 8.9Report and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which makes it possible to combine study with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Kubernetes K3s, AWS IoT Greengrass, Azure IoT Edge, Eclipse Mosquitto, Argo CD, in free, academic or evaluation versions. Tests are studied using real load-testing procedures on an MQTT broker, GitOps deployment on edge nodes, and disconnected gateway operation. Assessment is continuous, module by module, plus the final integrative project.

Accreditable laboratories(EN ISO/IEC 17025) with a rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-oriented Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:lecturers with experience in the training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, with cyber-OT, DIH and compliance as its pillars.
Capstone project

Build it end to end

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

Use case and requirements

Analyse reference architectures for IoT systems.

Logical and physical architecture

Select messaging protocols suited to each case.

Selection of protocols and platforms

Deploy containerised applications on edge nodes.

Edge processing design

Integrate devices with cloud-based IoT platforms.

Security and deployment plan

Automate deployment using infrastructure as code and GitOps.

Career opportunities

Where this takes you

IoT Solutions ArchitectCloud EngineerEdge Computing EngineerDevOps EngineerIoT Platform DeveloperDigital Transformation Consultant
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. A university degree is not required.
  • Internet connection and a computer capable of running the programme's software.
  • Sufficient Spanish to follow technical regulatory texts.

Ready to start?

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

FAQ

Frequently asked questions

The programme totals 800 hours, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.

The programme uses Kubernetes K3s, AWS IoT Greengrass, Azure IoT Edge, Eclipse Mosquitto and Argo CD. Free, academic or evaluation versions are used, and the tutor indicates the open-source alternative where one exists.

A SEIUM Institute diploma on passing the continuous assessment and the integrative project. It is in-house training, not an official qualification from the Ministry.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised towards the higher-level programme. Check the recognition policy when you enrol.

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