Diploma in Real-Time Monitoring and Data Analytics
Online postgraduate diploma of 800 hours in real-time monitoring and data analytics. 8 modules covering data acquisition, IoT protocols and architectures, time-series storage, stream processing, analytics and anomaly detection, visualisation and alerting, and data quality, security and governance, with an assigned technical tutor.
Diploma in Real-Time Monitoring and Data Analytics — studying from Australia
Defence is one of Australia's largest engineering employers, with major programmes in land systems, naval platforms, aircraft and integrated systems managed through the Department of Defence. Land systems engineering supports armoured vehicles, weapons and logistics equipment, often through prime contractors and local industry partners. Industry involvement is strongly encouraged through the Defence industry policy framework. Engineers work on sustainment, capability development, systems integration and safety assurance, typically in Canberra, Adelaide, Melbourne and regional defence precincts.
Fees for Australia: A$2,850 (AUD), with instalments and employer sponsorship available.
Relevant bodies in Australia
Typical roles
Questions from Australia
How does defence engineering recognition work in Australia?
Defence engineering in Australia is largely run through the Department of Defence and its industry partners, which set their own security clearance and qualification requirements. Engineers Australia is the professional body for accreditation. SEIUM's private qualifications are not accredited by these bodies, so recognition is for employers or the relevant body to decide.
Which Australian employers hire in defence and land systems?
Australia has defence prime contractors, the Department of Defence, and specialist land systems firms. Many of these roles require Australian security clearances, which depend on citizenship and background checks rather than course completion. Ask employers how they weigh private qualifications against experience and clearance requirements.
Is the course manageable with a job, and does it need a visa?
The programmes are 100% online and taught in English, so you can study from Australia without a student visa. Specialist courses take 300 hours, diplomas 800 and master's 1,900. An assigned technical tutor supports you, fees are payable in instalments, and employer sponsorship may be 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
Design real-time data acquisition and transmission architectures.
Apply standardised industrial and IoT protocols.
Manage time-series databases.
Process data streams using streaming platforms.
Develop anomaly detection and predictive analytics models.
Build dashboards and alerting systems.
Ensure data quality, security and governance.
Who it's for
- Industrial data engineers.
- Monitoring analysts.
- Data scientists.
- SCADA systems engineers.
- IoT architects.
- Data-driven reliability engineers.
- Engineering or science graduates looking to move into the defence sector.
What you'll work with
- ISO 13374 (condition monitoring data processing)
- ISO 17359 (condition monitoring and diagnostics of machines)
- IEC 62541 (OPC UA)
- ISO 55000 (asset management)
- IEC 62443 (industrial cybersecurity)
- ISO/IEC 27001 (information security management)
- ISO 8000 (data quality)
- Grafana
- InfluxDB
- Apache Kafka
- Node-RED
- Python (pandas, scikit-learn)
8 modules
1.1Sensors and transducers1.2Signal conditioning1.3Sampling and aliasing1.4Acquisition systems1.5Time synchronisation1.6Edge computing1.7Fieldbus protocols1.8Signal quality1.9Calibration and traceability1.10Practical exercise: configuring an acquisition system
2.1OPC UA2.2MQTT2.3Modbus and legacy protocols2.4Reference architectures2.5Edge gateways2.6Industrial wireless networks2.7Information models2.8Semantic interoperability2.9Scalability2.10Lab: publishing data with OPC UA and MQTT
3.1Characteristics of time series3.2InfluxDB and TimescaleDB3.3Retention policies3.4Compression and downsampling3.5Time-based queries3.6Data lakes3.7Data warehouses3.8Metadata and catalogues3.9Performance and scaling3.10Practical exercise: data modelling in InfluxDB
4.1Lambda and kappa architectures4.2Apache Kafka4.3Processing with Flink and Spark Streaming4.4Time windows4.5Rules and complex event processing4.6Latency and throughput4.7Fault tolerance4.8Flow orchestration4.9Node-RED for prototyping4.10Lab: data flow with Kafka
5.1Exploratory analysis of time series5.2Filtering and smoothing5.3Statistical anomaly detection5.4Isolation forests5.5Autoencoders5.6Forecasting models5.7Fault diagnosis5.8Model explainability5.9Model deployment5.10Practical exercise: anomaly detection in vibration data
6.1Dashboard design6.2Grafana6.3Key performance indicators6.4Alarm management following good practice6.5Alarm fatigue6.6Notifications and escalation6.7Automated reports6.8Geospatial visualisation6.9User experience6.10Workshop: operational dashboard with Grafana
7.1Data quality to ISO 80007.2Data lineage7.3Cybersecurity to IEC 624437.4Access control7.5Encryption in transit and at rest7.6Backups7.7Data governance7.8Data in classified environments7.9Regulatory compliance7.10Case study: audit of a monitoring system
8.1Definition of the monitored system8.2Data architecture8.3Implementation of data acquisition8.4Streaming pipeline8.5Analytical model8.6Dashboard8.7Security analysis8.8Evaluation of results8.9Report and presentation8.10Final project: final 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. There are no fixed timetables: you progress at your own pace within the intake, so the programme fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Grafana, InfluxDB, Apache Kafka, Node-RED and Python (pandas, scikit-learn), in free, academic or evaluation versions. Exercises are based on real procedures: designing a real-time sensor data pipeline, anomaly detection in time series and building an operational dashboard. Assessment is continuous by module, plus the final project.
Standards covered: ISO 13374, ISO 17359, IEC 62541, ISO 55000, IEC 62443, ISO/IEC 27001, ISO 8000.
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
- Prior technical training or professional experience in the sector. No university degree is 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.
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 Grafana, InfluxDB, Apache Kafka, Node-RED and Python (pandas, scikit-learn), 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 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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