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Postgraduate DiplomaEnergy and Networks Applications open

Postgraduate Diploma in Non-Technical Loss and Fraud Analytics

Online 800-hour Postgraduate Diploma in Non-Technical Loss and Fraud Analytics. 8 modules covering Royal Decree 1955/2000 (distribution and supply activities), Law 24/2013 (electricity sector) and Python (scikit-learn). Assigned tutor and open enrolment.

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

What you will be able to do

01

Classify technical and non-technical losses in distribution.

02

Calculate the technical losses of the network.

03

Prepare and combine data sources for detection.

04

Train machine learning models to detect anomalies.

05

Plan efficient inspection campaigns.

06

Design fraud recovery and prevention measures.

07

Apply ethical principles and data protection.

Profile

Who it's for

  • Non-technical loss analyst who wants to specialise in Non-Technical Loss and Fraud Analytics.
  • Distribution data scientist who wants to specialise in Non-Technical Loss and Fraud Analytics.
  • Inspection campaign manager who wants to specialise in Non-Technical Loss and Fraud Analytics.
  • Distribution network engineer who wants to specialise in Non-Technical Loss and Fraud Analytics.
  • Energy anti-fraud analyst who wants to specialise in Non-Technical Loss and Fraud Analytics.
  • Energy recovery manager who wants to specialise in Non-Technical Loss and Fraud Analytics.
  • Engineering or science graduates seeking to join electricity distribution companies.
Standards & tools

What you'll work with

  • Royal Decree 1955/2000 (distribution and supply activities)
  • Law 24/2013 (electricity sector)
  • Royal Decree 1110/2007 (metering points)
  • IEC 61968-9 (metering interfaces)
  • Regulation (EU) 2016/679 (GDPR)
  • ISO 37301 (compliance management systems)
Syllabus

8 modules · 800 h

  1. 1.1Technical versus non-technical losses
  2. 1.2Energy balance of the network
  3. 1.3Scale of losses by region
  4. 1.4Economic and regulatory impact
  5. 1.5Regulatory incentives for reduction
  6. 1.6Types of fraud: bypasses, tampering and illegal connections
  7. 1.7Metering and management errors
  8. 1.8Customers without contracts and unregistered consumption
  9. 1.9Legal aspects of electricity theft
  10. 1.10Case study: loss balance of an urban area
  1. 2.1Losses in conductors and transformers
  2. 2.2Load flows in low voltage
  3. 2.3Estimation using load profiles
  4. 2.4No-load and load losses
  5. 2.5Network models and GIS quality
  6. 2.6Calculation tools
  7. 2.7Balances per transformer substation
  8. 2.8Uncertainty in the calculation
  9. 2.9Separation of technical and non-technical losses
  10. 2.10Laboratory: calculation of technical losses in a LV circuit
  1. 3.1Smart meter load curves
  2. 3.2Meter events: cover opened and magnetic field
  3. 3.3Balances with totalising meters
  4. 3.4Commercial and billing data
  5. 3.5Data from previous inspections
  6. 3.6Geographic and socioeconomic data
  7. 3.7Data quality and cleansing
  8. 3.8Derived variables and feature engineering
  9. 3.9Labelling and inspection bias
  10. 3.10Practice: building a detection dataset
  1. 4.1Expert rules and thresholds
  2. 4.2Unsupervised anomaly detection
  3. 4.3Supervised classification with gradient boosting
  4. 4.4Neural networks on load curves
  5. 4.5Class imbalance and appropriate metrics
  6. 4.6Validation and overfitting prevention
  7. 4.7Model interpretability
  8. 4.8Graph and neighbourhood models
  9. 4.9Continuous model updating
  10. 4.10Laboratory: fraud classifier with XGBoost
  1. 5.1Prioritising inspections by expected value
  2. 5.2Campaign performance and hit rate
  3. 5.3Logistical planning of inspection teams
  4. 5.4Field inspection procedures
  5. 5.5Collection of evidence and reports
  6. 5.6Inspector safety
  7. 5.7Feedback to the model
  8. 5.8Effectiveness indicators
  9. 5.9Management of repeat offences
  10. 5.10Workshop: prioritised campaign plan
  1. 6.1Re-billing of energy taken fraudulently
  2. 6.2Regulatory settlement procedure
  3. 6.3Legal actions and complaints
  4. 6.4Technical anti-fraud measures
  5. 6.5Elevated meters and sealed boxes
  6. 6.6Concentric cables and twisted networks
  7. 6.7Social programmes and regularisation
  8. 6.8Communication with the public
  9. 6.9Coordination with authorities
  10. 6.10Case study: regularisation programme in vulnerable neighbourhoods
  1. 7.1Data protection in customer analytics
  2. 7.2Bias and discrimination in models
  3. 7.3Transparency towards the regulator
  4. 7.4Governance of risk models
  5. 7.5Algorithm auditing
  6. 7.6Proportionality of inspections
  7. 7.7Liability for false positives
  8. 7.8High-risk AI regulation
  9. 7.9Culture of integrity in the organisation
  10. 7.10Practice: bias assessment of a detection model
  1. 8.1Diagnosis of losses in the area
  2. 8.2Calculation of technical losses
  3. 8.3Data preparation
  4. 8.4Development of the detection model
  5. 8.5Design of the inspection campaign
  6. 8.6Prevention measures
  7. 8.7Economic analysis of the programme
  8. 8.8Monitoring indicators
  9. 8.9Report and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

Training 100 % online 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 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 (scikit-learn), QGIS, SQL, Power BI, in free, academic or evaluation versions. Tests are studied using real procedures for energy balances per transformer substation, targeted inspection campaigns and validation of detection models. Assessment is continuous by module, plus the final integrative project.

Accreditable laboratories(EN ISO/IEC 17025) with rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-driven Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:instructors with experience in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, with OT cyber security, DIH and compliance as its 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 losses in the area

Classify technical and non-technical losses in distribution.

Calculation of technical losses

Calculate the technical losses of the network.

Data preparation

Prepare and combine data sources for detection.

Development of the detection model

Train machine learning models to detect anomalies.

Design of the inspection campaign

Plan efficient inspection campaigns.

Career opportunities

Where this takes you

Non-technical loss analystDistribution data scientistInspection campaign managerDistribution network engineerEnergy anti-fraud analystEnergy recovery manager
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 Spanish to follow technical regulatory reading.

Ready to start?

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

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FAQ

Frequently asked questions

The programme comprises 800 hours in total, spread over 6 to 8 months. That is between 10 and 15 hours a week on average, compatible with a full-time job.

You work with Python (scikit-learn), QGIS, SQL and Power BI. Free, academic or evaluation versions are used, and the tutor indicates the open-source alternative where one exists.

A SEIUM own diploma on passing the continuous assessment and the integrative project. It is in-house training, not an official qualification from the Ministry.

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

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