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Diploma in Wearables and Performance Data in Actuarial Science

Online postgraduate diploma of 800 hours in wearables and performance data in actuarial science. 8 modules covering wearable devices and health data, data processing, physical activity and risk, actuarial modelling, interactive insurance products, legal and ethical framework and programme governance, 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

Diploma in Wearables and Performance Data in Actuarial Science — studying from India

India's construction, mining, agriculture and material handling sectors drive demand for off-road and special vehicles. Manufacturers such as Tata Motors, Ashok Leyland, Escorts Kubota, Mahindra & Mahindra and Bharat Earth Movers operate significant production facilities across the country. Industrial clusters in Pune, Coimbatore, Chennai and Jamshedpur support this sector with strong supplier networks. Standards and safety requirements are referenced through the Bureau of Indian Standards and the Ministry of Road Transport and Highways. Engineers in this area design hydraulic systems, drivetrains, operator interfaces and equipment for demanding field conditions.

Fees for India: ₹95,000 (Indian Rupee), with instalments and employer sponsorship available.

Relevant bodies in India

  • Bureau of Indian Standards (BIS)
  • Society of Indian Automobile Manufacturers (SIAM)
  • Automotive Research Association of India (ARAI)
  • Indian Council of Agricultural Research (ICAR)

Typical roles

  • Off-Highway Vehicle Engineer
  • Hydraulics Engineer
  • Agricultural Machinery Engineer
  • Construction Equipment Engineer

Questions from India

Which bodies in India approve off-road and special vehicles?

Vehicle approval in India involves the Automotive Research Association of India (ARAI) and Automotive Industry Standards under the Central Motor Vehicles Rules. Construction and agricultural machinery have their own sector standards through the Bureau of Indian Standards. SEIUM's qualification is private and not accredited by a national body, so it does not give approval status.

Which employers in India hire for off-road and machinery engineering?

Tractor, construction equipment and defence vehicle manufacturers, plus mining and agricultural machinery firms, are typical employers. Each sets its own hiring criteria and decides what weight to give a private qualification. Hands-on experience usually carries significant weight alongside any course you complete.

Can I study this online from India while working, and in what language?

Yes, the programme is 100% online, so you can study from any part of India without a student visa, fitting study around work. It is taught entirely in English, so you need a working level of the language. Each student has a technical tutor, and fees can be paid in instalments or sponsored by an employer.

Virtual lab · try it before you enrol

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Learning outcomes

What you will be able to do

01

Know wearable devices and the data they generate.

02

Process device data with quality and security.

03

Relate physical activity to biometric risk.

04

Incorporate activity data into actuarial models.

05

Design interactive insurance products.

06

Comply with the legal and ethical framework for using health data.

07

Evaluate and govern wearable-based programmes.

Profile

Who it's for

  • Life and health actuaries.
  • Insurance data scientists.
  • Insurance product designers.
  • Data protection officers.
  • Digital health analysts.
  • Wellness programme managers.
  • Engineering or science graduates seeking to enter life insurance.
Standards & tools

What you'll work with

  • Regulation (EU) 2016/679 (GDPR) (General Data Protection Regulation)
  • Directive 2009/138/EC (Solvency II) (EU insurance solvency framework)
  • Regulation (EU) 2024/1689 (EU Artificial Intelligence Act)
  • Regulation (EU) 2017/745 (medical devices)
  • Directive (EU) 2016/97 (IDD) (Insurance Distribution Directive)
  • ISO/IEC 27001 (information security management)
  • Law 50/1980 (Spanish Insurance Contract Act)
  • R
  • Python with pandas
  • Apple HealthKit
  • Google Health Connect
  • Microsoft Power BI
Syllabus

8 modules

  1. 1.1Device types: bands, watches, patches
  2. 1.2Sensors: accelerometer, PPG, ECG
  3. 1.3Variables: steps, heart rate, sleep
  4. 1.4Heart rate variability
  5. 1.5Device accuracy and validation
  6. 1.6Medical devices versus consumer devices
  7. 1.7Regulation (EU) 2017/745
  8. 1.8Data platforms and APIs
  9. 1.9Digital health ecosystems
  10. 1.10Workshop: comparing devices and variables
  1. 2.1Ingesting device data
  2. 2.2Cleaning and missing values
  3. 2.3Time synchronisation
  4. 2.4Daily and weekly aggregation
  5. 2.5Detection of manipulated data
  6. 2.6Data quality and bias
  7. 2.7Secure storage
  8. 2.8Cloud architectures
  9. 2.9Data governance
  10. 2.10Practical exercise: cleaning activity data in Python
  1. 3.1Epidemiological evidence on activity
  2. 3.2Sleep and mortality
  3. 3.3Fitness indicators
  4. 3.4Sedentary behaviour and morbidity
  5. 3.5Risk models with lifestyle variables
  6. 3.6Causation versus correlation
  7. 3.7Selection and self-selection
  8. 3.8Effect of the programme on behaviour
  9. 3.9Impact evaluation
  10. 3.10Case study: relationship between activity and sick leave
  1. 4.1Generalised linear models with activity data
  2. 4.2Survival models
  3. 4.3Credibility and experience
  4. 4.4Machine learning in pricing
  5. 4.5Validation and stability
  6. 4.6Model explainability
  7. 4.7Dynamic pricing
  8. 4.8Reserves and solvency
  9. 4.9Stress testing
  10. 4.10Lab: mortality model with activity variables in R
  1. 5.1Life insurance with wellness programmes
  2. 5.2Health insurance with incentives
  3. 5.3Group insurance for companies
  4. 5.4Rewards and discounts
  5. 5.5Design of behavioural incentives
  6. 5.6Gamification
  7. 5.7Customer retention
  8. 5.8User experience
  9. 5.9Market cases
  10. 5.10Practical exercise: designing an interactive life product
  1. 6.1GDPR and health data
  2. 6.2Explicit consent
  3. 6.3Data minimisation and purpose limitation
  4. 6.4Regulation (EU) 2024/1689 on artificial intelligence
  5. 6.5Non-discrimination in insurance
  6. 6.6Transparency towards the customer
  7. 6.7IDD Directive and product governance
  8. 6.8Device cyber security
  9. 6.9Ethics committees
  10. 6.10Workshop: data protection impact assessment
  1. 7.1Programme success indicators
  2. 7.2Experiments and control groups
  3. 7.3Cost-benefit analysis
  4. 7.4Model monitoring
  5. 7.5Product governance
  6. 7.6Reports to management
  7. 7.7Relationship with device providers
  8. 7.8Operational risk management
  9. 7.9Continuous improvement
  10. 7.10Case study: evaluation of a pilot programme
  1. 8.1Definition of the insured group
  2. 8.2Selection of data and devices
  3. 8.3Data processing
  4. 8.4Risk model
  5. 8.5Product design
  6. 8.6Legal and ethical assessment
  7. 8.7Evaluation plan
  8. 8.8Conclusions
  9. 8.9Report and presentation
  10. 8.10Final project: final 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: you progress at your own pace within each intake, so you can combine it with work.

Each module combines theory, guided reading of the original regulation and applied exercises. The working software is R, Python with pandas, Apple HealthKit, Google Health Connect and Microsoft Power BI, in free, academic or evaluation versions. Procedures are studied on real cases of risk modelling with activity data, design of interactive insurance products and evaluation of wellness programmes with control groups. Assessment is continuous by module plus the final project.

Standards covered: Regulation (EU) 2016/679 (GDPR), Directive 2009/138/EC (Solvency II), Regulation (EU) 2024/1689, Regulation (EU) 2017/745, Directive (EU) 2016/97 (IDD), ISO/IEC 27001, Law 50/1980.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of the GDPR, Solvency II and the EU AI Act applied to real cases, not as a theoretical annex.
Industry software:R, Python with pandas, Apple HealthKit, Google Health Connect, Microsoft Power BI, in free, academic or evaluation versions.
Final project:a wearable-based insurance proposal for a defined insured group, from data processing and risk modelling to product design and a legal, ethical and evaluation plan, 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.

Insured group and data
Define the insured group and select the devices and data variables.
Data processing
Clean, synchronise and aggregate the activity data in Python.
Risk model
Build a risk model incorporating activity variables in R.
Product and compliance
Design the interactive product and assess it against the GDPR and AI Act.
Final project
Present the proposal with its evaluation plan in a documented report, reviewed by your tutor.
Career opportunities

Where this takes you

Life and health actuaryInsurance data scientistInsurance product designerData protection officerDigital health analystWellness programme manager
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. A university degree is not required.
  • 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.

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 R, Python with pandas, Apple HealthKit, Google Health Connect, Microsoft Power BI, 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 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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