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Master'sAutonomous, ADAS & Software-Defined Vehicle Applications open

Master’s in OTA, Diagnostics & Operations Engineering

Online master's programme of 1,900 hours in OTA, diagnostics and operations engineering, structured in 12 modules covering OTA updates and update chain security, UDS and DoIP diagnostics, fleet telemetry, predictive maintenance, field quality, software operations, edge and cloud, operational cybersecurity and data regulation (UN ECE R156, ISO 24089, ISO 14229-1), 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 secure OTA architectures for the connected vehicle.

02

Implement SUMS in compliance with R156 and ISO 24089.

03

Apply UDS and DoIP diagnostic protocols.

04

Build fleet telemetry pipelines.

05

Develop predictive maintenance models.

06

Manage software operations and cybersecurity across the fleet.

07

Develop a connected vehicle operations project.

Profile

Who it's for

  • OTA engineers responsible for software update systems.
  • Diagnostics engineers working with UDS, DoIP and remote diagnostics.
  • Telematics engineers developing connected vehicle services.
  • Fleet operations managers overseeing vehicles in service.
  • Field quality data analysts working with warranty and fleet data.
  • Cloud platform engineers building automotive backends.
  • Engineering or science graduates seeking to enter the automotive sector.
Standards & tools

What you'll work with

  • UN ECE R156 (software updates and update management systems)
  • ISO 24089 (road vehicles – software update engineering)
  • ISO 14229-1 (unified diagnostic services (UDS))
  • ISO 13400-2 (diagnostic communication over IP (DoIP))
  • UN ECE R155 (cybersecurity management systems)
  • ISO/SAE 21434 (road vehicle cybersecurity engineering)
  • Regulation (EU) 2023/2854 (Data Act) (EU rules on fair access to and use of data)
  • ISO 22900-2 (modular vehicle communication interface (D-PDU API))
  • Vector CANoe
  • AWS IoT FleetWise
  • Eclipse Mosquitto
  • Uptane
  • Grafana
Syllabus

12 modules · 1900 h

  1. 1.1Life cycle of the connected vehicle
  2. 1.2On-board telematics and TCU units
  3. 1.3Manufacturer's connected services
  4. 1.4Fleet operations throughout the vehicle life
  5. 1.5Relationship between OTA, diagnostics and data
  6. 1.6Manufacturer's backend architecture
  7. 1.7Regulation driving connectivity
  8. 1.8After-sales business models
  9. 1.9Organisation of vehicle operations
  10. 1.10Case study: operations of a connected fleet
  1. 2.1Update types: firmware, software and data
  2. 2.2Full and partial ECU updates
  3. 2.3A/B architectures and partitions
  4. 2.4Differential updates and compression
  5. 2.5Orchestration of multi-ECU updates
  6. 2.6Safe installation conditions
  7. 2.7Recovery from update failures
  8. 2.8User experience of the update
  9. 2.9Data and bandwidth costs
  10. 2.10Lab: A/B update on an embedded board
  1. 3.1Regulation R156 and the SUMS
  2. 3.2The ISO 24089 standard
  3. 3.3The Uptane framework for automotive
  4. 3.4Package signing and verification
  5. 3.5Rollback protection
  6. 3.6Update server security
  7. 3.7RXSWIN software identification
  8. 3.8Configuration compatibility management
  9. 3.9Evidence for type approval
  10. 3.10Practical: Uptane test repository
  1. 4.1The UDS protocol ISO 14229
  2. 4.2Diagnostics over IP (DoIP)
  3. 4.3Fault codes and snapshots
  4. 4.4Regulatory OBD diagnostics
  5. 4.5ODX diagnostic description
  6. 4.6Remote diagnostics from the backend
  7. 4.7Secure diagnostics and authentication
  8. 4.8Workshop tools
  9. 4.9Diagnostics of ADAS systems
  10. 4.10Workshop: UDS session with CANoe
  1. 5.1In-vehicle data collection
  2. 5.2MQTT protocols and transmission
  3. 5.3Bandwidth management
  4. 5.4Triggers and smart sampling
  5. 5.5Mass ingestion platforms
  6. 5.6Time-series storage
  7. 5.7Data quality and completeness
  8. 5.8Privacy and consent
  9. 5.9Connectivity costs
  10. 5.10Lab: MQTT pipeline to a time-series database
  1. 6.1Component degradation models
  2. 6.2Remaining useful life prognosis
  3. 6.3Battery state of health across the fleet
  4. 6.4Anomaly detection in signals
  5. 6.5Machine learning for failures
  6. 6.6Integration with the workshop network
  7. 6.7Management of preventive campaigns
  8. 6.8Economic assessment of predictive maintenance
  9. 6.9Industry success stories
  10. 6.10Practical: battery remaining useful life model
  1. 7.1Early detection of quality problems
  2. 7.2Warranty analysis
  3. 7.3Management of recall campaigns
  4. 7.4Communication with authorities
  5. 7.5Root cause analysis with fleet data
  6. 7.6Regulatory post-market monitoring
  7. 7.7In-service quality indicators
  8. 7.8Feedback to engineering
  9. 7.9Management of serious incidents
  10. 7.10Case study: detection of a software defect
  1. 8.1Fleet configuration management
  2. 8.2Planning of update campaigns
  3. 8.3Staged and canary deployments
  4. 8.4Monitoring of update success
  5. 8.5In-service version management
  6. 8.6Withdrawal of defective versions
  7. 8.7Support for older vehicles
  8. 8.8Coordination with dealerships
  9. 8.9Operations metrics
  10. 8.10Workshop: staged deployment plan
  1. 9.1In-vehicle versus cloud processing
  2. 9.2Vehicle edge architectures
  3. 9.3Automotive cloud platforms
  4. 9.4MEC computing in 5G networks
  5. 9.5State synchronisation between vehicle and cloud
  6. 9.6Digital twin of the vehicle
  7. 9.7Backend scalability
  8. 9.8Resilience to loss of connectivity
  9. 9.9Infrastructure costs
  10. 9.10Lab: vehicle digital twin in AWS IoT
  1. 10.1The VSOC operations centre
  2. 10.2Intrusion detection across the fleet
  3. 10.3In-service vulnerability management
  4. 10.4Cybersecurity incident response
  5. 10.5Automotive threat intelligence
  6. 10.6Coordination with Auto-ISAC
  7. 10.7Regulatory incident notifications
  8. 10.8Response exercises
  9. 10.9Operational security metrics
  10. 10.10Practical: fleet response playbook
  1. 11.1The European Data Act regulation
  2. 11.2GDPR in connected services
  3. 11.3Third-party access to vehicle data
  4. 11.4Data for independent repair
  5. 11.5eCall and legal requirements
  6. 11.6EDR and DSSAD recorders
  7. 11.7Data retention and deletion
  8. 11.8Transparency towards the user
  9. 11.9Regulatory trends in data
  10. 11.10Case study: data portal for workshops
  1. 12.1Definition of the fleet and services
  2. 12.2OTA and SUMS architecture
  3. 12.3Remote diagnostics strategy
  4. 12.4Telemetry pipeline
  5. 12.5Predictive maintenance model
  6. 12.6Software operations plan
  7. 12.7Operational cybersecurity plan
  8. 12.8Conclusions and roadmap
  9. 12.9Thesis 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. There are no fixed timetables: you progress at your own pace within each intake, making it compatible with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Vector CANoe, AWS IoT FleetWise, Eclipse Mosquitto, Uptane and Grafana, in free, academic or evaluation versions. Testing is studied through real procedures: UDS and DoIP diagnostic sessions, staged update campaigns and fleet data analysis for quality. Assessment is continuous for each module, plus the final Master's Thesis.

Standards covered: UN ECE R156, ISO 24089, ISO 14229-1, ISO 13400-2, UN ECE R155, ISO/SAE 21434, Regulation (EU) 2023/2854 (Data Act), ISO 22900-2.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of UN ECE R156, ISO 24089 and ISO 14229-1 applied to real cases, not as a theoretical annex.
Industry software:Vector CANoe, AWS IoT FleetWise, Eclipse Mosquitto, Uptane and Grafana, in free, academic or evaluation versions.
Master's Thesis with defence:a complete connected vehicle operations project, from OTA and SUMS architecture and remote diagnostics to telemetry, predictive maintenance and operational cybersecurity, 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.

Secure OTA update
Implement an A/B update on an embedded board backed by an Uptane repository.
Diagnostic session
Run a UDS diagnostic session with CANoe and design the remote diagnostics strategy.
Telemetry pipeline
Build an MQTT pipeline into a time-series database with smart sampling triggers.
Predictive maintenance and operations
Model battery remaining useful life and plan a staged update deployment.
Master's Thesis
A complete connected vehicle operations project, from OTA and SUMS architecture and remote diagnostics to telemetry, predictive maintenance and operational cybersecurity, defended before a panel.
Career opportunities

Where this takes you

OTA engineerDiagnostics engineerTelematics engineerFleet operations managerField quality data analystCloud platform engineer
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 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 Vector CANoe, AWS IoT FleetWise, Eclipse Mosquitto, Uptane and Grafana, 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 degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the 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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