Diploma in Integration of Technical Assistants in Operations
Online postgraduate diploma of 800 hours in integrating technical assistants into operations, structured in 8 modules covering use cases, integration with ERP, MES and CMMS, operational context, interaction design, safety and human oversight, deployment and organisational change, with an assigned technical tutor.
Diploma in Integration of Technical Assistants in Operations — studying from Canada
Canada is a recognised centre for artificial intelligence research, with hubs in Toronto, Montréal and Edmonton supported by institutes such as the Vector Institute, Mila and Amii. Engineering teams across manufacturing, energy, finance and transport apply simulation, machine learning and data analytics to real operational problems. The federal government's Pan-Canadian AI Strategy and privacy regulation shape how organisations handle data. Typical employers include technology firms, banks, aerospace and automotive companies, and public research bodies.
Fees for Canada: C$2,010 (Canadian dollar), with instalments and employer sponsorship available.
Relevant bodies in Canada
Typical roles
Questions from Canada
Do Canadian bodies recognise data or AI qualifications from private institutes?
Data and AI roles in Canada are generally not licensed in the way engineering is, so recognition depends on employers and professional communities rather than a regulator. Engineering licensing through provincial associations applies only to engineering titles. SEIUM's qualifications are private, not official state degrees and not accredited by a national body, so employers decide how much weight to give them.
Do Canadian employers hire for data and AI skills, and would this help?
Canada has a large and active data and AI sector, with notable hubs in Toronto, Montreal and Vancouver, and employers hire widely for these skills. They usually look first at portfolios, technical interviews and proven projects. A SEIUM final project can demonstrate your ability, but a private qualification's value is decided by each employer, so present it alongside concrete work.
Is this manageable with a job, and what level of English is needed?
Because the programmes are fully online, you can study from home around your job, and no student visa is needed. Specialist courses are 300 hours, postgraduate diplomas 800 and master's 1,900, so plan your weekly time. Teaching is in English, so strong written and reading English is important. Instalment payments and possible employer sponsorship can help with funding.
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
Identify operational processes with potential for technical assistants.
Integrate assistants with ERP, MES and CMMS through APIs and connectors.
Build operational context from documentation and asset data.
Design interactions suited to plant and field technicians.
Apply human oversight and OT cybersecurity to operational agents.
Measure the impact of assistants with maintenance indicators.
Plan organisational adoption in line with AI regulations.
Who it's for
- AI engineers applying their skills to industrial operations.
- Industrial integration architects.
- Plant digital transformation managers.
- Digital maintenance engineers.
- Product owners of AI solutions.
- Industry 4.0 consultants.
- Engineering or science graduates seeking to enter industry and manufacturing.
What you'll work with
- Regulation (EU) 2024/1689 (Artificial Intelligence Act)
- IEC 62443 (security of industrial automation and control systems)
- ISO/IEC 42001:2023 (AI management systems)
- ISO 14224 (equipment reliability and maintenance data)
- ANSI/ISA-95 (enterprise-control system integration)
- ISO 9241-110:2020 (interaction principles)
- Regulation (EU) 2016/679 (General Data Protection Regulation)
- Law 31/1995 (Spanish Occupational Risk Prevention Act)
- LangGraph
- Microsoft Copilot Studio
- SAP Business Technology Platform
- Langfuse
- Node-RED
8 modules
1.1Typology: copilots, chatbots and agents1.2Use cases in maintenance, quality and production1.3Mapping candidate operational processes1.4Task analysis of operators and technicians1.5Functional and non-functional requirements1.6Value and ROI estimation1.7Operational risks of automation1.8Selecting models and providers1.9Reference architecture1.10Workshop: opportunity map for a plant
2.1Integration with ERP and SAP2.2MES systems and production data2.3CMMS: SAP PM, Maximo and work orders2.4REST and GraphQL APIs2.5Model Context Protocol and connectors2.6Function calling with typed schemas2.7OAuth 2.0 authentication and delegation2.8Queues and asynchronous processing2.9Error handling and retries2.10Practical exercise: an assistant that queries work orders
3.1Integrating sensor and historian data3.2Asset context according to ISO 142243.3Technical documentation and procedures3.4Retrieval augmentation over manuals3.5Plant knowledge graphs3.6Real-time versus historical data3.7Quality and currency of context3.8Permissions by role and area3.9Source traceability3.10Lab: asset context for fault diagnosis
4.1Conversational interfaces for the plant4.2Voice in noisy environments4.3Mobile devices and rugged tablets4.4Augmented reality for guidance4.5Plain language and step-by-step procedures4.6Confirmations and reversible actions4.7Handling uncertainty in responses4.8Accessibility and multilingualism4.9Testing with field technicians4.10Case study: conversational flow for a permit to work
5.1Assistant autonomy levels5.2Human in the loop and approvals5.3Functional safety and action limits5.4OT cybersecurity according to IEC 624435.5Prompt injection in operational environments5.6Logging and auditing of actions5.7Change management according to MOC procedures5.8Task risk assessment5.9Responding to assistant failures5.10Workshop: risk analysis of a maintenance agent
6.1Pilots and controlled trials6.2Indicators: MTTR, search time and adoption6.3Evaluating response quality6.4Observability and traces6.5Inference costs and optimisation6.6Edge and on-premise deployment6.7Scaling to multiple plants6.8Operator feedback6.9Continuous improvement of the assistant6.10Practical exercise: pilot dashboard
7.1Training operators and technicians7.2Managing resistance to change7.3Roles and responsibilities in operational AI7.4Relationship with health and safety committees7.5Consulting workers' representatives7.6Managing tacit knowledge7.7AI governance in the company7.8Compliance with the AI Act7.9Adoption roadmap7.10Case study: multi-plant adoption plan
8.1Selecting the process and users8.2Architecture and integration design8.3Preparing the operational context8.4Prototype implementation8.5User testing8.6Risk analysis and oversight8.7Deployment plan and metrics8.8Pilot value analysis8.9Report and presentation8.10Final project: final review with the tutor
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 the intake, making it compatible with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is LangGraph, Microsoft Copilot Studio, SAP Business Technology Platform, Langfuse, Node-RED, in free, academic or evaluation versions. Tests are studied on real procedures: integrating an assistant with maintenance work orders, assistant pilots with field technicians, and risk analysis of agents that act on systems. Assessment is continuous by module plus the final capstone project.
Standards covered: Regulation (EU) 2024/1689 on Artificial Intelligence, IEC 62443, ISO/IEC 42001:2023, ISO 14224, ANSI/ISA-95, ISO 9241-110:2020, Regulation (EU) 2016/679 (GDPR), Spanish Law 31/1995 on Occupational Risk Prevention.
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's 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 LangGraph, Microsoft Copilot Studio, SAP Business Technology Platform, Langfuse and Node-RED, 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 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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