TRAINING PROGRAMME

Advancing AI & LLM Integration for Mobility Businesses

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An applied AI programme for mobility consultancies and operators, using LLMs to analyse fleet data and tenders, benchmark KPIs, and produce client-ready deliverables faster.
COURSE OVERVIEW

Turning everyday mobility business work into confident, well-judged use of AI.

This course targets professionals at mobility consultancies, start-ups, technology providers, and transport operators — working in management, strategy, consulting, and analyst roles. Typical job titles include mobility consultant, transport planner, strategy analyst, project manager, and business development manager.

Training Format

Hybrid: online and in-person workshops.

Hours

5-6h (core modules)

Language

All training will be in English, with Portuguese and Spanish translations available.  

Certificate

A certificate from EIT Urban Mobility. is awarded upon completion of the online course(s).

Who is this course for?

Who is AIM4Mobility addressed to?


The course is aimed at professionals at mobility consultancies, start-ups, technology providers, and transport operators.

Required skills:
  • Professional experience in urban mobility or transport — familiarity with industry artefacts (e.g., SUMPs, EU directives, transport tenders) from work experience

Recommended (optional):
  • Familiarity with EU regulatory frameworks relevant to mobility
  • Experience producing consulting reports

Not required:
  • Programming, data science, or statistics
  • Formal AI/ML knowledge — the course assumes zero structured AI knowledge; learners may have used ChatGPT casually but have no framework for systematic LLM application

Tool requirements: 
  • Free-tier, browser-based AI tools. No paid subscriptions, API access, or locally installed software required.

Interested in learning how to use LLM and AI more effectively in urban mobility?

Enjoy the early bird discount while it lasts. 50€ 25€

COURSE OBJECTIVES

At the end of the course you'll be able to

What will the participants get from the course

Through a structured learning journey, mobiLLITY aims to:

Understand

how LLMs work and identify their key limitations for commercial and operational mobility contexts.

Use

advanced prompting patterns for data analysis tasks (CSV/Excel), report generation, and workflow automation.

Use LLMs

to explore fleet operations data, summarise performance metrics, and draft improvement recommendations.

Evaluate

and verify AI-generated outputs with professional accountability for commercial deliverables.

Apply LLMs

to analyse tender documents, compare city-level transport KPIs (Eurostat), and draft proposals and reports.

Design (optional capstone) 

an AI-assisted workflow for a real company mobility challenge.

MOBILLITY METHODOLOGY

A two-part journey: learn online, then apply it in person.

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MobiLLITY for Companies is delivered in two parts: a self-paced online course that every participant completes, and two optional in-person workshops that participants can add once they've finished at least one online course.

MODULES

Step 1 · For everyone

The online course

Self-paced — everyone completes this part

5–6htotal time
6modules
~5minper lecture
  • Micro-lectures, quizzes and applied tasks — no live attendance required
  • Built on real industry artefacts: EU directives, SUMPs, tenders, Eurostat KPIs, fleet data
  • Free-tier, browser-based AI tools only — no paid subscriptions or installs
  • Certificate on completing 5 core modules + exam; optional capstone earns Gold distinction
Step 2 · Optional
Optional

The in-person workshops

Apply what you've learned, face to face

2cities
~8heach, full day
Limitedavailability
  • Prerequisite: completion of at least one MobiLLITY online course
  • Two workshops – Lisbon, Portugal (30 September 2026) and Las Rozas, Spain (12 November 2026)
  • Full-day, in person — limited availability
  • Hands-on application of your AI and data skills to real challenges
See full workshop details

MobiLLITY does not cover travel costs.

Course structure and modules

The course is organised into six modules, following a shared linear path — all sub-profiles take the same modules in the same order, progressing from foundational understanding through applied tasks to critical evaluation and workflow integration.


Total duration: ~5-6 hours | Lectures: 26 | Micro-lecture duration: ~5 minutes

MODULE 1 – LLM Foundations for Mobility Professionals

Focus: Calibrating trust before applied work begins

This module covers how LLMs work, their key limitations, and trust calibration for commercial mobility contexts.

Key Themes: Common failure modes and the importance of verification in professional deliverables.

Outcome: A realistic, calibrated sense of what LLMs can be trusted to do in commercial and operational mobility work.

MODULE 2 – Fleet Data & Service Analysis

Focus: From raw operations data to recommendations

This module applies LLMs to fleet operations data.

Key Themes: Exploring fleet operations data, summarising performance metrics, identifying patterns, and drafting improvement recommendations using LLMs.

Outcome: Ability to move from raw fleet data to clear, LLM-assisted performance insights and recommendations.

MODULE 3 – Tenders, Benchmarking & Client Communication

Focus: Research, tenders, and client-facing deliverables

This module tackles the highest-adoption task family in the companies survey: research, tenders, and client-facing work.

Key Themes: Analysing tender documents, comparing city-level transport KPIs (Eurostat), competitive intelligence, and producing client-facing deliverables.

Outcome: Ability to use LLMs to accelerate tender analysis, benchmarking, and client communication with confidence.

MODULE 4 – Prompting for Productivity

Focus: Advanced prompting for data and reporting

This module builds advanced prompting competency that applies across both data analysis and document-production task families.

Key Themes: Advanced prompting patterns for data analysis (CSV/Excel), report generation, and workflow automation, covering role prompts, few-shot examples, chain-of-thought, and iterative refinement.

Outcome: A reusable toolkit of prompting patterns for day-to-day productivity tasks.

MODULE 5 – Evaluating & Trusting AI Outputs

Focus: The quality gate

This module addresses the number one barrier identified for companies: quality and reliability concerns.

Key Themes: Error detection, verification workflows, hallucination identification, cross-checking strategies, and professional accountability in commercial deliverables.

Outcome: A systematic verification habit that protects the quality of commercial deliverables.

MODULE 6 – Capstone (optional Gold Distinction)

Focus: Synthesis and professional accountability

The Capstone is where theory meets a real company mobility challenge, designed for those seeking a Gold Distinction.

Key Themes: Designing an AI-assisted workflow for a real company mobility challenge, integrating skills from all five core modules into a self-directed project.

Outcome: documented, repeatable workflow demonstrating tool selection, prompt strategy, verification steps, and professional accountability — usable immediately in the learner's professional work.

WORKSHOPS

Apply what you've learned online, in person.

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Both workshops are full-day, hands-on sessions open to any MobiLLITY audience once you've completed at least one online course. The workshops are optional, and availability is limited, so register early. If you're interested, you can choose between Lisbon or Las Rozas, whichever works better for you. 

MODULES

Workshop 1 30 September 2026

Lisbon, Portugal

Developed with ANSR, Portugal's road safety authority — turning institutional mobility and road safety data into clear visual outputs and stakeholder-ready communications.

Format
In person, full day (~8h)
Participants
Limited availability
Language
Portuguese
Data used
ANSR & public road safety data
The day in four stages
  1. 1 Data preparation — cleaning and structuring data with LLM help
  2. 2 Exploratory analysis — natural-language queries to surface patterns
  3. 3 Visualisation & communication — charts and outputs for decision-makers
  4. 4 Data privacy & responsible use — redaction and what free-tier tools can see
Workshop 2 12 November 2026

Las Rozas, Spain

Teaches a general data analysis workflow, then gives mixed teams the space to apply it to their own professional role.

Format
In person, full day (~8h)
Participants
Limited availability
Language
English
Data used
Eurostat KPIs, GTFS feeds, Barcelona IRIS
A two-part day
  1. 1 Shared foundation (~4h) — everyone works the same data analysis pipeline together
  2. 2 Role-specific application (~4h) — small groups apply it to their own domain (planning, communications, policy, operations)

Brought to you by:

FACTUAL Consulting

Leading mobility innovation consultancy.

XVAL

Experts in AI solutions for urban systems and education

EIT Urban Mobility

With the support of EIT Urban Mobility, this programme bridges the gap between cutting-edge tech and practical urban challenges.

CERTIFICATE OF COMPLETION

Once you complete the course, you'll have the opportunity to receive a certificate of completion signed by the course organizers, all of whom are recognized in the mobility industry.

Interested in learning how to use LLM and AI more effectively in urban mobility?

Enjoy the early bird discount while it lasts. 50€ 25€
This project is supported by EIT Urban Mobility, an initiative of the European Institute of Innovation and Technology (EIT), a body of the European Union. EIT Urban Mobility acts to accelerate positive change on mobility to make urban spaces more liveable. Learn more: eiturbanmobility.eu

This project is supported by EIT Urban Mobility, an initiative of the European Institute of Innovation and Technology (EIT), a body of the European Union.
EIT Urban Mobility acts to accelerate positive change on mobility to make urban spaces more liveable. Learn more: eiturbanmobility.eu