Postgraduate DiplomaAutomotive & Motorsport Applications open

Postgraduate Diploma in Data QA and Calibration in a Racing Environment

Online 800 h Postgraduate Diploma in Data QA and Calibration in a Racing Environment. 8 modules covering ISO/IEC 25012, ISO 8000-8 and Python (pandas, scikit-learn). Dedicated tutor and open enrolment.

Duration800 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma

Postgraduate Diploma in Data QA and Calibration in a Racing Environment — studying from South Africa

The automotive sector is one of South Africa's most important manufacturing industries, with major plants in the Eastern Cape around Gqeberha, in KwaZulu-Natal and in Gauteng. Manufacturers such as Mercedes-Benz South Africa, Ford and Volkswagen South Africa operate assembly and component facilities that export vehicles and parts across Africa and beyond. The sector relies on engineers skilled in powertrain design, vehicle dynamics, quality and production systems. Motorsport activity, including circuits at Kyalami and Zwartkops, adds further demand for performance engineering.

Fees for South Africa: R 20 400 (South African rand), with instalments and employer sponsorship available.

Relevant bodies in South Africa

  • National Association of Automobile Manufacturers of South Africa (NAAMSA)
  • South African Bureau of Standards (SABS)
  • Automotive Business Council (ABC)

Typical roles

  • Automotive Design Engineer
  • Powertrain Engineer
  • Vehicle Dynamics Engineer
  • Production Engineer

Questions from South Africa

Which South African bodies recognise automotive engineering skills, and does SEIUM count?

Professional recognition for engineers in South Africa runs through ECSA, which registers engineers, technicians and technologists under the Engineering Profession Act. Automotive trades also fall under bodies such as the MERSETA for skills development. SEIUM is a private online institute whose qualifications are not state degrees and are not accredited by a national body, so whether they are recognised is up to the employer or the relevant body to decide.

Will this programme help me find work in South Africa's automotive or motorsport industry?

South Africa has a significant automotive manufacturing and component sector, and motorsport teams and suppliers also hire engineers. Employers typically look at practical experience, recognised qualifications and references. A private online qualification can strengthen your profile in specialist areas, but it does not guarantee employment. Speak to potential employers about whether they would value it.

How does the course fit around a job, and how are fees paid?

The programme is delivered entirely online in English, with an assigned technical tutor and a final project. Master's programmes are 1,900 hours, postgraduate diplomas 800 hours and specialist courses 300 hours, so choose the level that matches your available time. Fees are payable in instalments, and employer sponsorship may be possible. Ask your employer whether they would fund part of the training.

Virtual lab · try it before you enrol

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Learning outcomes

What you will be able to do

01

Define data quality dimensions and indicators.

02

Automate the validation of telemetry channels.

03

Calibrate sensors in the garage environment.

04

Synchronise and align data from different sources.

05

Manage the configuration of acquisition systems.

06

Detect anomalies using statistical methods and machine learning.

07

Implement continuous quality improvement processes.

Profile

Who it's for

  • Competition data engineer looking to specialise in Data QA and Calibration in a Racing Environment.
  • Data quality engineer looking to specialise in Data QA and Calibration in a Racing Environment.
  • Data acquisition technician looking to specialise in Data QA and Calibration in a Racing Environment.
  • Instrumentation engineer looking to specialise in Data QA and Calibration in a Racing Environment.
  • Data analyst looking to specialise in Data QA and Calibration in a Racing Environment.
  • Performance engineer looking to specialise in Data QA and Calibration in a Racing Environment.
  • Engineering or science graduates looking to enter motorsport.
Standards & tools

What you'll work with

  • Standards-based learning: each module works with the standards and regulations that apply to the field.
  • Hands-on practical work with industry-standard software, simulation and real case studies.
  • Evidence-oriented final project: technical file, test plan, compliance dossier and operating limits.
  • Industry mentoring: faculty with professional experience in the field.
  • 100% online, international cohorts and support from SEIUM Career Services.
  • Ethics and safety: a safety-by-design approach, cybersecurity and regulatory compliance as pillars.
Syllabus

8 modules · 800 h

  1. 1.1Quality dimensions: accuracy, completeness, timeliness
  2. 1.2Impact of erroneous data on decisions
  3. 1.3Sources of error in acquisition
  4. 1.4Data quality according to ISO/IEC 25012
  5. 1.5Telemetry data versus logger data
  6. 1.6Metadata and session context
  7. 1.7Responsibilities of the data team
  8. 1.8Quality indicators per session
  9. 1.9Quality culture in the garage
  10. 1.10Case study: wrong decision due to corrupted data
  1. 2.1Physical range rules per channel
  2. 2.2Detection of jumps and discontinuities
  3. 2.3Detection of frozen channels
  4. 2.4Consistency checks between channels
  5. 2.5Validation of sampling frequencies
  6. 2.6Management of gaps and data loss
  7. 2.7Flagging suspicious data
  8. 2.8Automatic reports after each session
  9. 2.9Adaptive thresholds per circuit
  10. 2.10Lab: Python channel validation script
  1. 3.1Zeroing procedures
  2. 3.2Calibration of suspension potentiometers
  3. 3.3Calibration of steering sensors
  4. 3.4Calibration of load cells
  5. 3.5Calibration of pressure sensors
  6. 3.6Verification of temperature sensors
  7. 3.7Recording calibration coefficients
  8. 3.8Recalibration frequency during the season
  9. 3.9Common calibration errors
  10. 3.10Practice: linear potentiometer calibration
  1. 4.1Clocks in loggers and ECUs
  2. 4.2GPS synchronisation
  3. 4.3Offsets between data sources
  4. 4.4Alignment by distance within a lap
  5. 4.5Correction of filter delays
  6. 4.6Fusion of video and telemetry data
  7. 4.7Interpolation and resampling
  8. 4.8Synchronisation validation
  9. 4.9Management of time zones and timestamps
  10. 4.10Workshop: aligning data from two sources
  1. 5.1Versioning of logger configurations
  2. 5.2Recording sensor changes
  3. 5.3Channel mapping per chassis
  4. 5.4Calibration databases
  5. 5.5Traceability of instrumented parts
  6. 5.6Managing multiple cars
  7. 5.7Configuration templates
  8. 5.8Review before each session
  9. 5.9Configuration auditing
  10. 5.10Case study: mapping error after a chassis change
  1. 6.1Statistical detection methods
  2. 6.2Control charts
  3. 6.3Physics-based model detection
  4. 6.4Unsupervised machine learning
  5. 6.5Autoencoders for time series
  6. 6.6False positives and their management
  7. 6.7Explainability of alerts
  8. 6.8Integration into the workflow
  9. 6.9Evaluating detector performance
  10. 6.10Practice: anomaly detector with Isolation Forest
  1. 7.1Standard operating procedures
  2. 7.2Pre-session checklists
  3. 7.3Post-event quality review
  4. 7.4Quality indicators per season
  5. 7.5Root cause analysis of errors
  6. 7.6Training of technical staff
  7. 7.7Incident management tools
  8. 7.8Internal data audits
  9. 7.9Quality improvement plan
  10. 7.10Case study: improvement plan after a season
  1. 8.1Diagnosis of quality status
  2. 8.2Definition of validation rules
  3. 8.3Sensor calibration plan
  4. 8.4Synchronisation procedure
  5. 8.5Configuration management system
  6. 8.6Anomaly detector
  7. 8.7Drafting operating procedures
  8. 8.8Evaluation of results
  9. 8.9Report and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and a dedicated technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which makes it possible to combine study with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (pandas, scikit-learn), MoTeC i2 Pro, McLaren ATLAS, Bosch WinDarab, MATLAB, in free, academic or evaluation versions. Case studies are based on real procedures for automatic post-session data validation, sensor calibration in the garage and logger configuration audits. Assessment is continuous across modules, plus a final integrating project.

Hands-on practical workwith industry-standard software, simulation, real case studies and guided practical exercises.
Evidence-oriented final project:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:faculty with professional experience in the field and in real industry projects.
Flexible format(100% online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, cybersecurity and regulatory compliance as pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Diagnosis of quality status

Define data quality dimensions and indicators.

Definition of validation rules

Automate the validation of telemetry channels.

Sensor calibration plan

Calibrate sensors in the garage environment.

Synchronisation procedure

Synchronise and align data from different sources.

Configuration management system

Manage the configuration of acquisition systems.

Career opportunities

Where this takes you

Competition data engineerData quality engineerData acquisition technicianInstrumentation engineerData analystPerformance 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's software.
  • Sufficient English to follow technical standards texts.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

FAQ

Frequently asked questions

The programme totals 800 hours, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.

The programme uses Python (pandas, scikit-learn), MoTeC i2 Pro, McLaren ATLAS, Bosch WinDarab and MATLAB. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

A SEIUM own diploma upon passing the continuous assessment and the integrating project. It is in-house training, not an official Ministry title.

Yes. Modules passed in a course or postgraduate diploma in the same area can be credited towards the advanced programme. Check the recognition policy when you enrol.

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