Course in Ethics in the Use of Computer Vision in UAS
Online 300-hour course in ethics in the use of computer vision in UAS. 6 modules covering Regulation (EU) 2024/1689 (AI Act, biometric identification), Regulation (EU) 2016/679 (GDPR) and OpenCV. Assigned tutor and open enrolment.
Take the controls.
Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Describe the computer vision techniques embedded in UAS.
Analyse the risks of identifying people from the air.
Evaluate the performance and reliability of detection models.
Apply data protection and AI regulations to UAS operations.
Identify sensitive uses and establish usage limits.
Incorporate privacy by design into vision systems.
Develop a responsible computer vision project in UAS.
Who it's for
- Computer vision engineer looking to specialise in Ethics in the Use of Computer Vision in UAS.
- UAS operator looking to specialise in Ethics in the Use of Computer Vision in UAS.
- Data protection officer looking to specialise in Ethics in the Use of Computer Vision in UAS.
- Data scientist looking to specialise in Ethics in the Use of Computer Vision in UAS.
- Biometric systems auditor looking to specialise in Ethics in the Use of Computer Vision in UAS.
- AI ethics consultant looking to specialise in Ethics in the Use of Computer Vision in UAS.
- Engineering or science graduates seeking to enter unmanned aviation.
What you'll work with
- Regulation (EU) 2024/1689 (AI Act, biometric identification)
- Regulation (EU) 2016/679 (GDPR)
- Implementing Regulation (EU) 2019/947 (UAS operations)
- Organic Law 3/2018 (LOPDGDD)
- ISO/IEC 19795-1 (biometric performance evaluation)
- Delegated Regulation (EU) 2019/945 (UAS)
6 modules · 300 h
1.1Detection, tracking and re-identification1.2Architectures: CNNs and vision transformers1.3Aerial imagery: scale, occlusion and perspective1.4Datasets: VisDrone and UAVDT1.5Onboard versus ground-based processing1.6Civil applications: inspection, agriculture and rescue1.7Police and military applications1.8Values in conflict1.9Dual-use technology and capability increases1.10Case study: tracking persons in mountain rescue
2.1Facial recognition from the air2.2Appearance and gait-based re-identification2.3Prohibitions under Regulation (EU) 2024/16892.4Biometric data under the GDPR2.5Error and demographic bias2.6Surveillance of demonstrations2.7Stigmatisation and chilling effect2.8Municipal moratoria2.9Privacy-preserving alternatives2.10Laboratory: automatic anonymisation in aerial video
3.1Metrics: mAP, MOTA and IDF13.2Adverse conditions: night, fog and rain3.3Thermal imaging and its interpretation3.4Domain shift between regions3.5Adversarial attacks using physical patches3.6Uncertainty and decision thresholds3.7Field testing and validation3.8Model documentation3.9Liability for errors3.10Practice: evaluating a detector on VisDrone
4.1Border surveillance and migrants' rights4.2Security at events and public spaces4.3Policing and public order control4.4Target selection in armed conflict4.5Human control over weapon systems4.6Legal review under Article 364.7Third-party data in conflict zones4.8Export to repressive regimes4.9Human rights due diligence4.10Case study: use of AI-vision drones at borders
5.1Privacy by design5.2Data minimisation and retention5.3Human oversight of detections5.4Logging and auditing5.5Public communication of capabilities5.6Fundamental rights impact assessment5.7Model publication and dual use5.8Ethics committees in universities5.9Standards and good practice5.10Workshop: impact assessment of an aerial surveillance system
6.1Defining the use case6.2Data and model selection6.3Training and evaluation6.4Bias analysis6.5Privacy assessment6.6Dual-use analysis6.7Safeguard design6.8Deployment recommendations6.9Report and presentation6.10Final review with the tutor
How you'll learn
100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: students progress at their own pace within the enrolment period, which makes it possible to combine the course with work.
Each module combines theory, guided reading of the original regulation and applied exercises. The working software is OpenCV, Python (PyTorch), Ultralytics YOLO, QGroundControl, in free, academic or evaluation versions. Practical work draws on real procedures for evaluating detection models on aerial imagery, data protection impact assessments, and performance testing across demographic groups. Assessment is continuous per module plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Describe the computer vision techniques embedded in UAS.
Analyse the risks of identifying people from the air.
Evaluate the performance and reliability of detection models.
Apply data protection and AI regulations to UAS operations.
Identify sensitive uses and establish usage limits.
Where this takes you
Requirements
- No prior degree required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow technical regulatory texts.
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 300 hours, spread over 3 to 5 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
The course uses OpenCV, Python (PyTorch), Ultralytics YOLO and QGroundControl. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An own diploma from SEIUM upon passing the continuous assessment and the integrative project. This is in-house training, not an official Ministry qualification.
Yes. Modules passed in a course or postgraduate diploma in the same area can be credited towards the advanced programme. Check the credit transfer policy when you enrol.
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