Apply now
Postgraduate DiplomaDesign, HMI & Product Applications open

Diploma in Experimentation and Data-Based Decision Making

Online postgraduate diploma of 800 hours in experimentation and data-driven decisions, structured in 8 modules covering statistics for experiments, A/B test design, advanced analysis, causal inference, experimentation in mobility and decision-making with ISO 3534-3, the GDPR and Python (statsmodels), with an assigned technical tutor.

Duration6–8 months
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

Formulate testable hypotheses and align them with business decisions.

02

Apply statistical fundamentals to experiment design.

03

Design A/B tests that are robust to common biases and errors.

04

Analyse experiments with advanced variance reduction techniques.

05

Estimate causal effects when experimentation is not possible.

06

Adapt experimentation to vehicles and mobility services.

07

Translate experimental results into documented decisions.

Profile

Who it's for

  • Data scientists specialising in experimentation.
  • Product analysts who design and read A/B tests.
  • Product managers who want decisions grounded in evidence.
  • Quantitative researchers working with observational data.
  • Decision analysts supporting leadership teams.
  • Engineers building experimentation platforms.
  • Engineering or science graduates seeking to enter digital product teams.
Standards & tools

What you'll work with

  • ISO 3534-3 (statistics – design of experiments vocabulary)
  • Regulation (EU) 2016/679 (General Data Protection Regulation)
  • ISO 3534-1 (statistics – general statistical terms and probability)
  • ISO 5725-2 (repeatability and reproducibility of measurement methods)
  • ISO/IEC 25012 (data quality model)
  • Regulation (EU) 2024/1689 (Artificial Intelligence Act)
  • Directive 2005/29/EC (unfair commercial practices)
  • Python (statsmodels)
  • R
  • GrowthBook
  • Optimizely
  • Eppo
Syllabus

8 modules

  1. 1.1Evidence-based decisions
  2. 1.2Cognitive biases in decision-making
  3. 1.3Hypotheses and the scientific method
  4. 1.4Hierarchy of evidence
  5. 1.5Experimentation in leading digital companies
  6. 1.6Experimentation maturity
  7. 1.7Ethics of experimenting with users
  8. 1.8Communicating uncertainty
  9. 1.9Decisions with incomplete data
  10. 1.10Workshop: formulating testable hypotheses
  1. 2.1Distributions and variability
  2. 2.2Hypothesis testing
  3. 2.3Interpreting the p-value
  4. 2.4Confidence intervals
  5. 2.5Statistical power and sample size
  6. 2.6Minimum detectable effect
  7. 2.7Type I and Type II errors
  8. 2.8The Bayesian approach to inference
  9. 2.9Multiple comparisons and correction
  10. 2.10Practical: sample size calculation
  1. 3.1Unit of randomisation
  2. 3.2Primary and guardrail metrics
  3. 3.3Duration and seasonality
  4. 3.4A/A calibration tests
  5. 3.5Sample ratio mismatch
  6. 3.6Novelty and learning effects
  7. 3.7Interference and network effects
  8. 3.8Multivariate and factorial tests
  9. 3.9Experimentation platforms
  10. 3.10Lab: designing an onboarding A/B test
  1. 4.1Variance reduction with CUPED
  2. 4.2Sequential analysis with early stopping
  3. 4.3Heterogeneity of treatment effects
  4. 4.4Ratio metrics and the delta method
  5. 4.5Bootstrap resampling of metrics
  6. 4.6Segment analysis
  7. 4.7Long-term effects
  8. 4.8Multi-armed bandit algorithms
  9. 4.9Meta-analysis of experiments
  10. 4.10Case study: analysing a test with sample ratio mismatch
  1. 5.1Observational data and confounding
  2. 5.2Difference in differences
  3. 5.3Regression discontinuity designs
  4. 5.4Instrumental variable estimation
  5. 5.5Propensity score matching
  6. 5.6Synthetic control method
  7. 5.7Bayesian structural time series
  8. 5.8Directed acyclic causal graphs
  9. 5.9Assumptions and limitations
  10. 5.10Practical: difference in differences with Python
  1. 6.1Experiments in connected vehicles
  2. 6.2Feature testing via OTA
  3. 6.3Fleet experiments
  4. 6.4Safety limits in experimentation
  5. 6.5Experiments in HMI studies
  6. 6.6Pricing experiments
  7. 6.7Geographic experiments by zone
  8. 6.8Experiments with small samples
  9. 6.9User trials in the laboratory
  10. 6.10Case study: testing an assistance feature in a fleet
  1. 7.1Decision frameworks
  2. 7.2Experiment review
  3. 7.3Learnings repository
  4. 7.4Communication to stakeholders
  5. 7.5Visualising results
  6. 7.6Opportunity cost
  7. 7.7Prioritising experiments
  8. 7.8Experimentation governance
  9. 7.9Typical decision errors
  10. 7.10Workshop: simulated decision committee
  1. 8.1Business problem
  2. 8.2Hypotheses and metrics
  3. 8.3Detailed experimental design
  4. 8.4Power calculation
  5. 8.5Analysis of results
  6. 8.6Complementary causal inference
  7. 8.7Decision recommendation
  8. 8.8Follow-up plan
  9. 8.9Report and presentation
  10. 8.10Final project: final review with the tutor
Methodology, software & labs

How you'll learn

The programme is 100% online 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 it fits around your job.

Each module combines theory, guided reading of the original standard and applied exercises. You work with Python (statsmodels), R, GrowthBook, Optimizely and Eppo, in free, academic or evaluation versions. Exercises are based on real procedures: design and analysis of A/B tests in digital products, causal inference studies with observational data and feature experiments in connected fleets. Assessment is continuous by module, plus the final integrating project.

Standards covered: ISO 3534-3, Regulation (EU) 2016/679, ISO 3534-1, ISO 5725-2, ISO/IEC 25012, Regulation (EU) 2024/1689, Directive 2005/29/EC.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of ISO 3534-3, ISO 3534-1 and the GDPR applied to real cases, not as a theoretical annex.
Industry software:Python (statsmodels), R, GrowthBook, Optimizely and Eppo, in free, academic or evaluation versions.
Final project:a complete experimentation study for a real business problem, from hypotheses and power calculation to analysis, causal inference and decision recommendation, reviewed by your tutor.
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.

Business problem and hypotheses
Frame a business problem and turn it into testable hypotheses and metrics.
Experimental design and power
Produce a detailed experimental design with its power calculation.
Analysis of results
Analyse the results and complement them with causal inference methods.
Decision recommendation
Translate the evidence into a documented decision and follow-up plan.
Final project
Present the complete experimentation study in a report and presentation, reviewed by your tutor.
Career opportunities

Where this takes you

Experimentation Data ScientistProduct AnalystData-Driven Product ManagerQuantitative ResearcherDecision AnalystExperimentation Platform Engineer
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. No university degree is required.
  • 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.

Apply now Scholarships
FAQ

Frequently asked questions

The programme totals 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with Python (statsmodels), R, GrowthBook, Optimizely and Eppo, 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 final project. 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 are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.

Prior technical training or professional experience in the sector (no university degree required), 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.

Keep exploring

Related programmes

See all in Design, HMI & Product
Postgraduate Diploma1,440 $

Diploma in HMI for Extended Operation (Rail/Marine)

Online postgraduate diploma of 800 hours in HMI for prolonged operation in rail and marine: 8 modules covering human factors in long-duration operation, operator vigilance systems,…

800 hours · 6–8 monthsOnlineDesign, HMI & Product
Postgraduate Diploma1,440 $

Diploma in Unreal/KeyShot for Review and Storytelling

Online postgraduate diploma of 800 hours in Unreal/KeyShot for design review and storytelling: 8 modules covering visualisation tools, KeyShot scenes, real-time review with Unreal Engine, visual…

6–8 monthsOnlineDesign, HMI & Product
Postgraduate Diploma1,220 $

Diploma in Service Design for EV and Customer Journey

Online postgraduate diploma of 800 hours in Service Design for EVs and Customer Journey. 8 modules covering the EV service ecosystem, the EV driver customer journey,…

6–8 monthsOnlineDesign, HMI & Product
Diploma in Experimentation and Data-Based Decision MakingEnrol
Related programmes

More in Design, HMI & Product

Diploma in Cabin Thermal Management and Occupant WellbeingView programme →Diploma in Human-Machine Interaction Assessment in the CockpitView programme →Diploma in Trim Processes, Joining and Perceived QualityView programme →Diploma in Usage Analytics and Experience ImprovementView programme →Diploma in Validation with SimRacing and Telemetry of UseView programme →Diploma in Design for Manufacturing and AssemblyView programme →

All Design, HMI & Product 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.