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

Master’s in Product, Regulation & Business Engineering

Online master's programme of 1,900 hours in product, regulation and business engineering for automated driving: 12 modules covering product management, the international regulatory framework, safety as a business requirement, business models, economics, technology strategy, market, liability and scaling, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
Enrol now View syllabus Ask an advisor
Virtual lab · try it before you enrol

Take the controls.

Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.

SIM · LIVE ●
Learning outcomes

What you will be able to do

01

Manage automated driving products.

02

Interpret the international regulatory framework.

03

Integrate safety as a business requirement.

04

Design business models for autonomy.

05

Evaluate the economics of autonomous driving.

06

Analyse the market and competition.

07

Develop a product and business project.

Profile

Who it's for

  • ADAS product managers.
  • Autonomous driving strategy managers.
  • Business analysts in the automotive sector.
  • Regulatory specialists.
  • Mobility consultants.
  • Business development directors.
  • Engineering or science graduates seeking to enter the automotive sector.
Standards & tools

What you'll work with

  • Regulation (EU) 2019/2144 (General Safety Regulation for vehicles)
  • Implementing Regulation (EU) 2022/1426 (type approval of automated driving systems)
  • UN ECE R157 (Automated Lane Keeping Systems)
  • ISO 26262 (road vehicle functional safety)
  • ISO 21448 (SOTIF — safety of the intended functionality)
  • ISO/SAE 21434 (road vehicle cybersecurity engineering)
  • Directive (EU) 2024/2853 (liability for defective products)
  • SAE J3016 (levels of driving automation)
  • Microsoft Excel
  • Power BI
  • Jira Product Discovery
  • Miro
  • Python
Syllabus

12 modules · 1900 h

  1. 1.1ADAS and autonomous driving value chain
  2. 1.2From series-production ADAS to the robotaxi
  3. 1.3Strategies of manufacturers and tech companies
  4. 1.4Product positioning by level
  5. 1.5Commercial success factors
  6. 1.6Customer perception and willingness to pay
  7. 1.7Software product life cycle
  8. 1.8Supplier ecosystem
  9. 1.9Market trends to 2035
  10. 1.10Case study: a manufacturer's product strategy
  1. 2.1Discovering customer needs
  2. 2.2Defining functions and requirements
  3. 2.3Product roadmap
  4. 2.4Prioritisation with the RICE and Kano frameworks
  5. 2.5ODD specification as a product decision
  6. 2.6Managing variants and markets
  7. 2.7Product metrics
  8. 2.8Stakeholder management
  9. 2.9Feature launch
  10. 2.10Lab: roadmap for an L2+ system
  1. 3.1The Geneva Agreements and the WP.29 Forum
  2. 3.2UNECE ADAS Regulations
  3. 3.3European General Safety Regulation
  4. 3.4European regulation of automated systems
  5. 3.5Federal and state regulation in the US
  6. 3.6Regulation in China and Japan
  7. 3.7Data and AI regulation
  8. 3.8Authorisation procedures
  9. 3.9Expected evolution of the framework
  10. 3.10Practical exercise: regulatory map by market
  1. 4.1Functional safety, SOTIF and cybersecurity
  2. 4.2Cost of safety in the product
  3. 4.3Safety arguments and communication
  4. 4.4Product liability
  5. 4.5Incident and recall management
  6. 4.6Consumer assessment programmes
  7. 4.7Safety and brand reputation
  8. 4.8Insurance and risk
  9. 4.9Safety as a differentiator
  10. 4.10Workshop: impact analysis of a recall
  1. 5.1Selling in-vehicle features
  2. 5.2Subscriptions and features on demand
  3. 5.3Robotaxi and mobility as a service
  4. 5.4Autonomy for logistics
  5. 5.5Software licensing to manufacturers
  6. 5.6Data as an asset
  7. 5.7Partnerships and joint ventures
  8. 5.8Unit economics of services
  9. 5.9Business model risks
  10. 5.10Lab: ADAS subscription model
  1. 6.1Cost of autonomy hardware
  2. 6.2Development and validation costs
  3. 6.3Cost of maps and data
  4. 6.4Fleet operating costs
  5. 6.5Cost learning curves
  6. 6.6Break-even point of services
  7. 6.7Funding in the sector
  8. 6.8Company valuation
  9. 6.9Sensitivity analysis
  10. 6.10Practical exercise: cost per kilometre of a robotaxi
  1. 7.1Sensor architectures and costs
  2. 7.2Make-or-buy decisions
  3. 7.3Computing platforms and suppliers
  4. 7.4Data and learning strategies
  5. 7.5Modular versus end-to-end approaches
  6. 7.6Intellectual property and patents
  7. 7.7Open standards and ecosystems
  8. 7.8Technology risk management
  9. 7.9Technology roadmap
  10. 7.10Workshop: make-or-buy analysis for perception
  1. 8.1Market segmentation
  2. 8.2Competitive analysis of players
  3. 8.3Barriers to entry
  4. 8.4Consolidation in the sector
  5. 8.5Opportunities in emerging markets
  6. 8.6Chinese manufacturers and their strategy
  7. 8.7Tier 1 suppliers and tech companies
  8. 8.8Start-ups and funding
  9. 8.9Market scenarios
  10. 8.10Case study: competitive analysis of robotaxis
  1. 9.1Public perception of autonomy
  2. 9.2Communicating capabilities
  3. 9.3Risks of overpromising
  4. 9.4Media crisis management
  5. 9.5Relations with authorities
  6. 9.6Community engagement
  7. 9.7Ethics and responsibility
  8. 9.8Labour impact of automation
  9. 9.9Equity of access
  10. 9.10Practical exercise: launch communication plan
  1. 10.1Civil liability for automated vehicles
  2. 10.2Product Liability Directive
  3. 10.3Contracts with software suppliers
  4. 10.4Service level agreements
  5. 10.5Insurance for autonomous fleets
  6. 10.6Risk allocation
  7. 10.7Data ownership
  8. 10.8Landmark litigation
  9. 10.9Legal trends in liability
  10. 10.10Workshop: contractual responsibility matrix
  1. 11.1Phased launch strategies
  2. 11.2Pilots and commercial trials
  3. 11.3Market selection
  4. 11.4Geographic expansion of the service
  5. 11.5Operations management
  6. 11.6Scaling the organisation
  7. 11.7Partnerships with cities
  8. 11.8Scaling indicators
  9. 11.9Lessons from deployments
  10. 11.10Case study: expansion plan to new cities
  1. 12.1Market and opportunity analysis
  2. 12.2Product definition
  3. 12.3Regulatory analysis by market
  4. 12.4Safety strategy
  5. 12.5Business model
  6. 12.6Economic and financial analysis
  7. 12.7Launch plan
  8. 12.8Conclusions and future work
  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. There are no fixed timetables: you progress at your own pace within each intake, making it compatible with full-time work.

Each module combines theory, guided reading of the original standards and applied exercises. The working software is Microsoft Excel, Power BI, Jira Product Discovery, Miro and Python, in free, academic or evaluation versions. Work is based on real procedures for market and competitive analysis, economic models of autonomous services and regulatory maps by market. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: Regulation (EU) 2019/2144 (General Safety), Implementing Regulation (EU) 2022/1426 (ADS), UN ECE R157, ISO 26262, ISO 21448, ISO/SAE 21434, Directive (EU) 2024/2853 (liability for defective products), SAE J3016.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of the General Safety Regulation, Implementing Regulation (EU) 2022/1426, UN ECE R157 and the Product Liability Directive applied to real cases, not as a theoretical annex.
Industry software:Microsoft Excel, Power BI, Jira Product Discovery, Miro and Python, in free, academic or evaluation versions.
Master's Thesis with defence:A complete product and business project for automated driving, from market analysis and product definition to regulation, safety strategy, business model and launch plan, 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.

Market and product
Analyse the market opportunity and define the product.
Regulation and safety
Carry out the regulatory analysis by market and define the safety strategy.
Business model
Design the business model for the product or service.
Economic analysis
Build the economic and financial analysis and the launch plan.
Master's Thesis
Present the conclusions of the product and business project, defended before a panel.
Career opportunities

Where this takes you

ADAS Product ManagerAutonomous Driving Strategy ManagerBusiness AnalystRegulatory SpecialistMobility ConsultantBusiness Development Director
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.

Apply now Scholarships
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 Microsoft Excel, Power BI, Jira Product Discovery, Miro and Python, 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.

Keep exploring

Related programmes

See all in Autonomous, ADAS & Software-Defined Vehicle
Master's6,610 $

Master’s in HARA, ASIL & Safety Case Engineering

Online master's programme of 1,900 hours in HARA, ASIL and safety case engineering, structured in 12 modules covering functional safety management, item definition, HARA, ASIL decomposition,…

1900 hOnlineAutonomous, ADAS & Software-Defined Vehicle
Master's6,610 $

Master’s in Autonomous Last-Mile Logistics Engineering

Online master's programme of 1,900 hours in autonomous last-mile logistics engineering: 12 modules covering sidewalk delivery robots, autonomous vans, delivery drones, navigation and perception, logistics optimisation,…

1900 hOnlineAutonomous, ADAS & Software-Defined Vehicle
Master's9,970 $

Master’s in Advanced Radar and LiDAR Processing Engineering

Online master's programme of 1,900 hours in advanced radar and LiDAR processing engineering. 12 modules covering radar signals and waves, radar processing, 4D imaging radar, LiDAR…

1900 hOnlineAutonomous, ADAS & Software-Defined Vehicle
Master’s in Product, Regulation & Business EngineeringEnrol
Related programmes

More in Autonomous, ADAS & Software-Defined Vehicle

Master’s in Highway Autonomy EngineeringView programme →Master’s in Robust Perception in Adverse Conditions EngineeringView programme →Master’s in International Regulation and Type Testing EngineeringView programme →Master’s in Validation, Simulation & Data EngineeringView programme →Master’s in Dev Platforms Engineering for SDVs — Vehicle-Centric APIs, App Stores, Sandboxing and PermissionsView programme →Master’s in Industrial OTA & SUMS EngineeringView programme →

All Autonomous, ADAS & Software-Defined Vehicle programmes → · How to apply · Fees & financing · Scholarships

Scroll to Top
SEIUM – Institute of Advanced Engineering
Powered by  GDPR Cookie Compliance
Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.