AI, Compliance & Digital Learning
Courses designed from the latest research on the AI Act, microlearning and AI-augmented pedagogy.
AI Compliance & AI Act — Complete Training
Master the world's first legal framework on AI. Microlearning course (3–7 min modules) for rapid and lasting adoption — target completion rate: 80%+.
Course Objectives
- Understand AI Act risk levels and compliance obligations for 2025–2026
- Identify and mitigate algorithmic bias in AI systems
- Master data governance: GDPR, system mapping, AI model cybersecurity
- Apply AI literacy (Article 4 of the AI Act) — legal obligation since February 2025
- Deploy real-time operational compliance through Just-in-Time Knowledge (LIFOW)
- Build a 2026 SME action plan using Bpifrance AI Booster funding schemes
Detailed Program
- Module 1: AI Act Regulatory Framework Fundamentals — Risk levels, sanctions, French context (CNIL/Arcom) (10h)
- Module 2: Ethics and Bias Mitigation — Algorithmic audits, fairness metrics, legal equity obligations (10h)
- Module 3: Data Governance and Security — System mapping, QMS documentation, cybersecurity, GDPR consent (12h)
- Module 4: Just-in-Time Operational Compliance (LIFOW) — IDE/CRM integration, real-world case studies, SME 2026 action plan (13h)
Prerequisites
No technical prerequisites. Open to any professional involved in creating, deploying, or using AI systems in a business context.
EnrollGenerative AI & Content Creation Automation
Since AI saves 30% of production time by automatically fragmenting dense content, train your teams to master these accelerated creation tools.
Course Objectives
- Use AI to transform archives (50-min videos, long PDFs) into educational micro-modules
- Generate smart infographics and automated simulations
- Master automatic fragmentation into quiz banks and adaptive assessments
- Reduce training content production time by 30%
- Produce short vertical videos (<60s) with AI tools (Runway, HeyGen, Synthesia)
Detailed Program
- Module 1: LLMs applied to educational content creation — GPT-4, Claude, Gemini (8h)
- Module 2: Automatic fragmentation of dense content into micro-modules (6h)
- Module 3: AI generation of infographics, quizzes and simulations (8h)
- Module 4: Advanced video learning — vertical formats, motion design, AI avatars (8h)
- Module 5: Accelerated production workflow — from archive to module in 30 minutes (5h)
Prerequisites
Regular use of digital tools. No technical AI skills required.
EnrollMicrolearning & Digital Learning Engineering
With 94% of organizations adopting microlearning in 2026, train your teams to design bite-sized content with 80%+ completion rates.
Course Objectives
- Design 3 to 7-minute bite-sized content focused on a single objective
- Master advanced video learning: vertical videos <60s and interactive motion design
- Develop gamification strategies to increase engagement by 60%
- Implement Spaced Repetition for 25 to 60% retention
- Achieve 80%+ completion rates vs 20% for classic e-learning
Detailed Program
- Module 1: Microlearning principles — Granularity, single objective, cognitive load (5h)
- Module 2: Modern formats — Vertical videos, flashcards, interactive motion design (8h)
- Module 3: Educational gamification — Points, badges, challenges, leaderboards (6h)
- Module 4: Spaced repetition & lasting memorization — Interval algorithms (6h)
- Module 5: Data-driven management — Completion rates, retention, continuous optimization (5h)
Prerequisites
Interest in pedagogy or professional training. No technical prerequisites.
EnrollWorkflow Automation — LIFOW (Learning in the Flow of Work)
Integrate knowledge directly into your teams' daily tools for immediate performance and frictionless adoption.
Course Objectives
- Integrate micro-training into daily tools: CRM, Slack, Teams, IDE
- Deploy Just-in-Time Knowledge — deliver the exact information when needed
- Build continuous learning pipelines integrated into business workflows
- Measure the impact of LIFOW on operational performance and adoption speed
Detailed Program
- Module 1: LIFOW concepts — From one-time training to continuous learning (5h)
- Module 2: Integration in CRMs and collaboration tools (8h)
- Module 3: Just-in-Time Knowledge — Contextual triggers and situational micro-units (8h)
- Module 4: LIFOW content architecture — Mapping tasks to learning resources (8h)
- Module 5: Impact measurement and continuous optimization (6h)
Prerequisites
Experience in training management or digital tool integration in a business environment.
EnrollAI Assistance Systems & Enterprise Chatbots
The future of education relies on conversational agents available 24/7. Deploy educational chatbots capable of detecting difficulties in real time.
Course Objectives
- Deploy educational chatbots capable of detecting employee difficulties in real time
- Build a 24/7 AI assistant integrated into business tools (CRM, LMS, IDE)
- Manage human–AI assistant interactions in an ethical professional framework
- Implement agents capable of suggesting micro-modules adapted to detected errors
- Measure the pedagogical effectiveness of AI assistants via behavioral data
Detailed Program
- Module 1: Conversational agent architecture — LLM, RAG, long-term memory (10h)
- Module 2: Deployment in enterprise tools — Slack, Teams, CRM, LMS (8h)
- Module 3: Real-time difficulty detection — Behavioral analysis and triggers (8h)
- Module 4: Ethics and governance of AI assistants — Transparency, limits, human supervision (6h)
- Module 5: Management and optimization — KPIs, feedback loops, continuous improvement (8h)
Prerequisites
Basic knowledge of LLMs or AI agents. Experience in development or digital solution architecture.
EnrollData Analysis & Cognitive Retention
Drive training with data: calculate optimal recall intervals to guarantee 25 to 60% retention, and target 80%+ microlearning completion rates.
Course Objectives
- Use data to calculate ideal spaced repetition intervals
- Guarantee 25 to 60% memory retention via Spaced Repetition algorithms
- Drive training by completion rates (target: 80%+)
- Analyze error patterns to adapt learning paths in real time
- Build actionable pedagogical performance dashboards
Detailed Program
- Module 1: Neuroscience of learning — Forgetting curve, cognitive load (5h)
- Module 2: Spaced Repetition algorithms — SM-2, FSRS, practical implementation (6h)
- Module 3: Learning Analytics — Collection, analysis and visualization of pedagogical data (8h)
- Module 4: Continuous data-driven optimization — A/B content testing, feedback loops (6h)
Prerequisites
Basic knowledge of data analysis. Curiosity for cognitive sciences and pedagogy.
Enroll