Master’s in Smart Metering and AMI Data Quality Engineering
Online master's programme of 1,900 hours in smart metering and AMI data quality engineering. 12 modules covering metrology, PLC and DLMS/COSEM communications, MDM and VEE, data quality, low-voltage analytics, non-technical losses and fraud, consumer analytics, cybersecurity and GDPR, and metering regulation, with an assigned technical tutor.
Master’s in Smart Metering and AMI Data Quality Engineering — studying from Canada
Canada's energy sector spans oil and gas in Alberta, hydroelectricity in Québec and Manitoba, nuclear generation in Ontario, and growing wind and solar capacity across several provinces. Transmission and distribution networks are operated by provincial utilities such as Hydro-Québec and Ontario Power Generation, alongside private operators. Grid modernisation, interconnection and energy efficiency are priority areas for engineers. Regulation is handled by provincial energy boards and the federal Canada Energy Regulator.
Fees for Canada: C$12,400 (Canadian dollar), with instalments and employer sponsorship available.
Relevant bodies in Canada
Typical roles
Questions from Canada
Who licenses energy and power network engineers in Canada?
Power and energy engineers in Canada usually obtain Professional Engineer licences from provincial associations, which regulate the use of the title and require accredited education and experience. SEIUM's qualifications are private, not official state degrees and not accredited by a national body, so they do not themselves grant licensing. Employers or relevant bodies decide recognition, so verify this first.
Do Canadian utilities and energy employers value this type of training?
Canadian utilities and energy firms, including those in Ontario, Alberta and Quebec, typically prioritise licensed engineers and verifiable operational experience. A SEIUM qualification may complement your profile, and a strong final project can help demonstrate skills, but its acceptance is for each employer to decide. Ask employers what they expect before enrolling.
Can I study alongside a job, and what about funding and language?
Yes, the programmes are fully online, so you can study from home without a student visa and plan sessions around work. Specialist courses are 300 hours, postgraduate diplomas 800 and master's 1,900. Instruction is in English, and each student has an assigned technical tutor. Fees can be paid in instalments, and employer sponsorship is possible.
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.
What you will be able to do
Explain the architecture and functions of an AMI system.
Apply the metrological principles of electricity metering.
Analyse PLC communications and DLMS/COSEM protocols.
Design validation and estimation processes for metering data.
Assess and improve AMI data quality.
Develop analytics for the low-voltage network and fraud detection.
Ensure the cybersecurity and privacy of metering data.
Who it's for
- Metering data analysts.
- Remote meter management engineers.
- Energy data quality specialists.
- Low-voltage engineers.
- Non-technical loss analysts.
- AMI systems architects.
- Engineering or science graduates aiming to move into electricity distribution.
What you'll work with
- Directive 2014/32/EU (Measuring Instruments Directive, MID)
- Royal Decree 1110/2007 (Spanish unified regulation on metering points)
- IEC 62056 (DLMS/COSEM)
- UNE-EN 50470-3 (static meters for active energy)
- IEC 62052-11 (electricity metering equipment: general requirements)
- Recommendation 2012/148/EU (preparations for the roll-out of smart metering systems)
- Regulation (EU) 2016/679 (GDPR)
- Implementing Regulation (EU) 2023/1162 (interoperability of metering and consumption data)
- Python (pandas, scikit-learn)
- Gurux DLMS
- Apache Spark
- Power BI
- QGIS
12 modules · 1900 h
1.1Evolution of electricity metering1.2Smart meter roll-out in Spain1.3European smart metering targets1.4Architecture of an AMI system1.5Functions of the smart meter1.6Benefits for the distribution company and the consumer1.7Second-generation meters1.8European roll-out experiences1.9Challenges of remote meter management1.10Case study: analysis of a Spanish distribution company's roll-out
2.1Principles of electronic metering2.2Accuracy classes2.3Measuring Instruments Directive2.4Periodic metrological verification2.5Reactive energy metering2.6Measurement of quality of supply2.7Three-phase and boundary meters2.8Registers and load profiles2.9Meter testing2.10Laboratory: verification of a meter on a test bench
3.1PRIME PLC and G3-PLC3.2Data concentrators3.3Cellular communications and NB-IoT3.4RF mesh networks3.5DLMS/COSEM application protocol3.6OBIS object model3.7Interference and PLC quality3.8Communication topology3.9Reading performance3.10Practical exercise: analysis of DLMS/COSEM frames
4.1Architecture of an MDM4.2Data acquisition (HES)4.3Validation, estimation and editing (VEE)4.4Validation rules4.5Estimation of missing data4.6Billing and settlement4.7Integration with corporate systems4.8Scalability and storage4.9Data auditing4.10Laboratory: VEE rules on hourly load curves
5.1Dimensions of data quality5.2Typical errors in AMI data5.3Outlier detection5.4Gaps and duplicates5.5Clock time drift5.6Topology inconsistencies5.7Quality indicators5.8Data governance5.9Continuous quality improvement5.10Practical exercise: data quality of a meter network
6.1Phase and connectivity identification6.2Impedance estimation6.3Low-voltage voltage profile6.4Broken neutral detection6.5Energy balance per secondary substation6.6Transformer loading6.7Detection of undeclared self-consumption6.8Low-voltage demand forecasting6.9Data-driven planning6.10Laboratory: identification of customer–transformer connectivity
7.1Types of electricity fraud7.2Energy balances7.3Tamper alarms7.4Machine learning models7.5Prioritisation of inspections7.6Effectiveness indicators7.7Legal aspects of fraud7.8International cases of loss reduction7.9Loss reduction7.10Case study: fraud detection model with AMI data
8.1Customer segmentation8.2Non-intrusive load monitoring (NILM)8.3Energy efficiency for households8.4Response to time-of-use tariffs8.5Energy poverty and data8.6Value-added services8.7Consumer access to data8.8Datadis and data platforms8.9Communicating information to customers8.10Practical exercise: segmentation of consumption profiles with clustering
9.1Threats to AMI systems9.2Security in DLMS/COSEM9.3Key management9.4Firmware updates9.5Concentrator security9.6GDPR and consumption data9.7Impact assessments9.8European privacy recommendations9.9Incident response9.10Workshop: risk assessment of an AMI system
10.1Metering point regulations10.2Meter reading operators10.3Reading and billing deadlines10.4Data exchange with suppliers10.5Internal market directive and metering10.6Metering for self-consumption10.7Metering for EV charging10.8Data interoperability10.9The role of the CNMC10.10Case study: supplier switching processes with AMI data
11.1Second-generation meters11.2Edge analytics in meters11.3Sub-metering in homes11.4Integration with distributed resources11.5Near-real-time metering11.6Open data platforms11.7Low-voltage digital twin11.8Artificial intelligence applications11.9Roadmap11.10Practical exercise: specification of a next-generation meter
12.1Definition of the use case12.2Inventory of AMI data12.3Quality assessment12.4Development of the analytical model12.5Validation of results12.6Integration into processes12.7Benefit assessment12.8Conclusions and future work12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
The programme is delivered 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 can be combined with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (pandas, scikit-learn), Gurux DLMS, Apache Spark, Power BI and QGIS, in free, academic or evaluation versions. Work is based on real procedures for validating hourly meter load curves, low-voltage connectivity analysis and fraud detection models. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: Directive 2014/32/EU, Royal Decree 1110/2007, IEC 62056, UNE-EN 50470-3, IEC 62052-11, Recommendation 2012/148/EU, Regulation (EU) 2016/679, Implementing Regulation (EU) 2023/1162.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- 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.
Frequently asked questions
The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Python (pandas, scikit-learn), Gurux DLMS, Apache Spark, Power BI and QGIS, 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 Master's Thesis. 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 in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A degree in engineering, science or architecture (or equivalent professional experience), 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.
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