Level 1 · Awareness · ½ to 1½ days

Understanding
Data &
AI

Fundamentals with no technical prerequisites — for informed decision-making

4 progressive modules that give every employee, manager, or executive the essential reference points to work with data and AI with full awareness — without unnecessary jargon.

C1 · Data Culture C2 · Understanding AI C3 · Responsible GenAI C4 · Agentic AI ✦ New
View Modules ↓ ← Back to Hub
This learning path at a glance
4
Modules
1½d
Total Duration
0
Prerequisites
All
Audiences
C1 · Data Culture & Business ½d
C2 · Understanding AI ½d
C3 · Responsible GenAI ½d
C4 · Agentic AI new ½d
Learning Sequence · 4 steps

A progressive learning journey

Each module builds on the previous one. C1 anchors the data mindset, C2 demystifies AI, C3 provides the responsible GenAI methodology, C4 opens the door to agentic AI — the next real challenge.

C1
Step 1 · Awareness All audiences
Data Culture & Business
Understanding what data is, my role in its quality, and why it truly matters.
½ day ▾
Program
What is business data?
  • Why this module — what "data culture" really means
  • What you produce every day — the invisible data
  • Classifying data — what I can do and what I cannot do
Quality & governance in daily work
  • Data quality — my concrete role
  • My role in governance — what everyone needs to know
  • The 8 data habits every employee should master
Deliverables & outcomes
  • 🗂️
    Personal classification card
    Each participant identifies and classifies their key data (public / internal / confidential / regulated)
  • ✅
    8 data habits checklist
    A daily reminder tool to embed good data practices into everyday work
  • 👤
    Data roles & contacts card
    Data Owner, Data Steward — who to contact, when, and why
📖
Self-Learning Module Available
Self Learning — C1 · Data Culture & Business
→
↓
data mindset → AI understanding
C2
Step 2 · AI Fundamentals All audiences
Understanding AI
Demystifying AI, understanding its real limitations and concrete use cases by business function.
½ day ▾
Program
What AI is (and is not)
  • The AI landscape — what actually exists today
  • The 3 critical limitations: hallucination, bias & opacity
  • AI in banking — real use cases by business function
My stance toward AI
  • What every employee needs to understand
  • The 3-check rule before any decision-grade use
  • Hands-on practice — recognize, evaluate, decide
Deliverables & outcomes
  • 🗺️
    AI landscape map — illustrated overview
    ML, LLM, generative AI, agentic AI — clear positioning of each type
  • ⚠️
    3 critical limitations grid
    Hallucination, algorithmic bias, opacity — how to detect and protect against them
  • 📋
    3-check verification rule
    Personal protocol for using AI responsibly in decision-making
📖
Self-Learning Module Available
Self Learning — C2 · Understanding AI
→
↓
understand → use responsibly
C3
Step 3 · Responsible practice All audiences
Responsible GenAI
CARE method, 5 critical risks, organizational AI policy and high-ROI use cases.
½ day ▾
Program
Method & risks
  • Why "responsible" — what is already happening in your organization
  • The CARE method — crafting a prompt that works
  • The 5 critical GenAI risks in a banking context
Policy & use cases
  • The responsible AI policy — what the organization must provide
  • GenAI in banking — high-ROI use cases by business function
  • Preview of C4: when GenAI becomes agentic
Deliverables & outcomes
  • 🎯
    CARE prompt template
    Context · Action · Result · Example — immediately actionable method
  • 🔍
    5 GenAI risks matrix
    Confidentiality, hallucination, bias, Shadow AI, regulatory compliance
  • 📊
    ROI use case mapping
    By business function — quick wins identified and prioritized
📖
Self-Learning Module Available
Self Learning — C3 · Responsible GenAI
→
↓
GenAI → agentic AI · new 2026
NEW MODULE · 2026
C4
Step 4 · Agentic opening New 2026 All audiences
Introduction to Agentic AI
Understanding what agentic AI truly changes — for processes, organizations, and governance.
½ day ▾
Program
From assistant to agent
  • LLM vs Agent — what fundamentally changes
  • The 4 gears of an AI agent: memory, tools, planning, action
  • Before/After by function — what agents change in your daily work
Risks & governance
  • The 3 critical agentic risks for decision-makers
  • What you can delegate to an agent and what you cannot yet
  • Bridge to M7: going deeper into architecture & governance
Deliverables & outcomes
  • 🤖
    LLM vs Agent comparison table
    8 dimensions of comparison — reference for non-technical decision-makers
  • ⚡
    Before/After process matrix
    By business function — what agents concretely change in workflows
  • 🛡️
    Agentic evaluation grid
    3 questions before entrusting a process to an AI agent
Going further
Module M7 — Agentic Architecture & Governance goes deeper into architecture, orchestration patterns and production deployment.
View Agentic AI Learning Path →
📖
Self-Learning Module Available
Self Learning — C4 · Introduction to Agentic AI
→
C1Data Culture
→
C2Understanding AI
→
C3Responsible GenAI
→
C4Agentic AI
1½ days
Total Duration
Tailored · In-Company Training
Train an entire team in data & AI culture?
This learning path is particularly suited for in-company training to level up data and AI literacy across all employees — regardless of their profile.
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