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Capability

Role-based AI Curriculum Design

Learning paths for executives, managers, specialists and technical teams, built from a skills analysis and your own processes rather than generic examples. The curriculum map runs from AI foundations and generative AI to agents, data, BI and automation, and every path states what participants must be able to do afterwards.

Training changes how people work only when it is designed around the work. We start from the roles and the processes, then choose the content.

01Architecture

Reference architecture

A typical arrangement of the components. Every implementation is adapted to your systems, data-residency and security requirements.

Audiences

  • Executives
  • Managers and specialists
  • Technical teams
Skills and role analysis

Curriculum map

  • AI foundations and responsible use
  • Generative AI and agentsOpenAI · Microsoft Copilot · Anthropic
  • Data, BI and automationPower BI · Power Automate · n8n
Learning paths per role

Delivery

  • Workshops and hands-on sessions
  • Exercises on your processes
Applied assignments

Evidence of learning

  • Practical assessment
  • Programme report
Components shown by layer, top to bottom, with what flows between them. Technologies are examples, chosen per project.

02Components

What this capability covers

  1. 01

    Skills and role analysis

    Current skills, responsibilities and target behaviours mapped per audience.

  2. 02

    Curriculum map

    Topics from AI foundations to agents, data, BI and automation, arranged into paths by role and level.

  3. 03

    Bilingual learning materials

    Exercises, cases and guides in Arabic and English, built on your own processes and documents.

  4. 04

    Assessment design

    Practical checks and applied assignments that show what participants can now do, not only what they remember.

03Implementation

How we implement it

The curriculum is designed with your HR or learning team and the managers of the participating groups. We agree the learning objectives per audience first, then select topics and exercises, and use your processes and documents as case material wherever confidentiality allows.

  • Every path states its objectives, level, format and time commitment.
  • Exercises run on approved tools and sample data, in line with your data-protection rules.
  • Materials are handed over so your team can run and update them.

04Deliverables

What you receive

  • Skills and role analysis

  • Curriculum map and learning paths

  • Bilingual participant materials

  • Assessment design and programme report

Technology

Technologies we work with

  • OpenAI
  • Microsoft Copilot
  • Gemini
  • Anthropic
  • Power BI
  • Power Automate
  • n8n
  • Python

Chosen per project and aligned with your existing standards. Listed as technologies we use, not as partnerships or endorsements.

05Use cases

Typical applications

Patterns this capability is designed for, not a list of delivered projects.

  1. 01

    Organisation-wide AI literacy

    A common baseline for all staff on what AI can do, where its limits are and the rules for using it.

  2. 02

    Manager and specialist paths

    Role-specific paths for teams expected to redesign their processes with AI.

  3. 03

    Technical upskilling

    Deeper paths for developers and data teams who will build and maintain AI solutions.

06Evidence

Related work

Projects and programmes in which this capability played a part, described with the role NLAI actually had.

  • Training programme

    AI Project Building Course — Cohort 9

    Cohort 9 of the AI Project Building Course was a three-day, in-person programme that NLAI delivered in a training partnership with EMC (Educational Mastar Central).

    Read more

07Related

More in Training & Capability Building

  • Hands-on AI Project Programmes

    Programmes in which teams build a working AI project on a real problem, following the CRISP-DM method from business understanding to evaluation and presentation.

Next step

Scope Role-based AI Curriculum Design for your organisation

Share your process, data and constraints. We will propose an approach, the evidence to collect first and a realistic plan.