Master’s in Product Management Engineering for Software-Defined Vehicles
Online master's programme of 1,900 hours in product management engineering for software-defined vehicles. 12 modules covering SDV architectures, the automotive PM role, discovery and requirements, in-vehicle UX, automotive DevOps, safety and regulation, OTA life cycle, monetisation, data and AI, ecosystem and roadmap governance, with an assigned technical tutor.
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Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Understand the architectures and platforms of the software-defined vehicle.
Define the vision, strategy and roadmap of automotive software products.
Specify traceable requirements based on user research.
Design safe user experiences that limit distraction.
Integrate functional safety, cybersecurity and type approval requirements.
Manage the software life cycle through OTA updates.
Evaluate monetisation models for vehicle features and data.
Who it's for
- Automotive software product managers.
- Product owners for connected features.
- Software platform managers.
- In-vehicle experience designers.
- Digital monetisation managers.
- Systems requirements engineers moving into product roles.
- Engineering or science graduates seeking to enter the automotive industry.
What you'll work with
- ISO 26262 (road vehicle functional safety)
- ISO/SAE 21434 (road vehicle cybersecurity engineering)
- UN Regulation No. 156 (software updates and software update management system)
- UN Regulation No. 155 (vehicle cybersecurity management system)
- ISO 21448 (safety of the intended functionality – SOTIF)
- Automotive SPICE 4.0 (automotive software process assessment)
- ISO/IEC/IEEE 29148 (requirements engineering)
- Regulation (EU) 2018/858 (vehicle type approval and market surveillance)
- Jira
- Siemens Polarion ALM
- Vector CANoe
- Figma
- dSPACE VEOS
12 modules · 1900 h
1.1From the mechanical to the software-defined vehicle1.2Centralised and zonal E/E architectures1.3On-board high-performance computers1.4Decoupling hardware and software1.5QNX, Linux and Android Automotive1.6On-board hypervisors and containers1.7Strategies of benchmark manufacturers1.8OEMs' own software platforms1.9New technology players1.10Case study: architecture of a current vehicle
2.1Responsibilities of the software PM2.2Product, platform and features2.3Relationship with systems engineering2.4Product owner versus product manager2.5Product vision and strategy2.6Stakeholders: brand, quality and homologation2.7Product in matrix organisations2.8Vehicle cycles versus software cycles2.9Product success metrics2.10Workshop: vision for a connected feature
3.1Vehicle user research3.2Driver and passenger needs3.3Product clinics with users3.4Functional and non-functional requirements3.5User stories and acceptance criteria3.6Regulatory requirements as product input3.7Requirements traceability3.8Requirements engineering according to ISO/IEC/IEEE 291483.9Prioritising features by value3.10Practical: specification of a remote parking feature
4.1HMI and driver distraction4.2NHTSA driver distraction guidelines4.3Voice interfaces and assistants4.4Screens, physical controls and haptics4.5Personalisation and user profiles4.6Integration with CarPlay and Android Auto4.7Accessibility in the cabin4.8Usability testing in a simulator4.9On-board experience metrics4.10Lab: usability of an infotainment system
5.1Scaled agility in the automotive industry5.2Continuous integration and delivery5.3MiL, SiL and HiL testing5.4Virtual ECUs and virtualisation5.5Automotive SPICE in agile environments5.6Variants and product lines5.7Software release trains5.8Software quality and DORA metrics5.9Traceability and collaboration tools5.10Workshop: CI/CD pipeline for an ECU
6.1Functional safety ISO 26262 at product level6.2SOTIF according to ISO 214486.3Cybersecurity: ISO/SAE 21434 and R1556.4Software updates and R1566.5Type approval: Regulation (EU) 2018/8586.6Automated driving and R1576.7Regulation (EU) 2022/1426 on automated vehicles6.8Privacy and the GDPR in the vehicle6.9The European Artificial Intelligence Act6.10Case study: regulatory impact of an ADAS feature
7.1OTA update strategy7.2Software versions across the fleet7.3Long-term hardware-software compatibility7.4Telemetry and observability7.5Software incidents in the field7.6Staged rollout and rollback7.7User experience during updates7.8Support over the vehicle's life7.9Obsolescence of computing hardware7.10Practical: rolling out a major update
8.1Features on demand and subscriptions8.2Recurring software revenue8.3Vehicle app stores8.4Vehicle data as a source of value8.5Pricing software features8.6Customer value perception8.7B2B models for fleets8.8Value sharing with partners8.9Business case for a software feature8.10Case study: revenue from an assisted driving feature
9.1Vehicle data platforms9.2The data loop for improving features9.3Feature usage analytics9.4A/B experimentation across fleets9.5Generative artificial intelligence in the cabin9.6Data quality and labelling9.7Data governance and consent9.8The Data Act and third-party access9.9Ethics of driver data9.10Lab: feature usage with fleet data
10.1Tier-1 and technology suppliers10.2The COVESA and Eclipse SDV consortia10.3Hyperscalers and the automotive cloud10.4Software licensing models10.5Open source and licence compliance10.6Software development contracts10.7Intellectual property in software10.8Vehicle APIs for external developers10.9The Chinese and US ecosystems10.10Workshop: evaluating partners for a cabin platform
11.1Platform and feature roadmaps11.2Alignment with the vehicle programme11.3Hardware dependencies11.4Product committees and decision-making11.5Feature portfolio11.6Product performance indicators11.7Communicating the roadmap11.8Managing technical debt11.9Organising by product teams11.10Practical: three-year roadmap for a platform
12.1Selecting the feature or platform12.2User and market research12.3Product definition and requirements12.4Regulatory and safety analysis12.5Architecture and technical dependencies12.6Business and monetisation model12.7Roadmap and launch plan12.8Success metrics and evaluation12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
A 100% online programme 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, so the programme fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Jira, Siemens Polarion ALM, Vector CANoe, Figma and dSPACE VEOS, in free, academic or evaluation versions. Exercises are based on real procedures: specifying a vehicle software feature, usability testing of a cabin system and the business case for a feature on demand. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: ISO 26262, ISO/SAE 21434, UN Regulation No. 156, UN Regulation No. 155, ISO 21448, Automotive SPICE 4.0, ISO/IEC/IEEE 29148, Regulation (EU) 2018/858.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer able to run 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.
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 Jira, Siemens Polarion ALM, Vector CANoe, Figma and dSPACE VEOS, 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, plus a computer able to run the programme 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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