AI IN BUSINESS

Description

This course provides a comprehensive understanding of artificial intelligence (AI) in business context, preparing future business leaders, entrepreneurs, and consultants, to leverage AI both for themselves and the companies they work for/ operate. Through a blend of theoretical foundations and hands-on practice, students will develop the understanding, mindset and practical skills needed to work with AI, identify AI opportunities, manage implementation risks, and lead AI initiatives in various organizational settings. The course emphasizes real-world applications across industries, combining traditional lectures with interactive workshops where students directly manipulate AI tools. Participants will learn to navigate the rapidly evolving AI ecosystem and develop actionable strategies for AI adoption. No academic/ professional prerequisite. Participating students will need a laptop with internet access. Thèmes clés / Key Topics: - AI fundamentals and business applications - Large Language Models (LLMs) and generative AI - AI ecosystem and business models - Implementation strategies and change management - Ethics, regulations, and governance - Emerging AI technologies: agents, reasoning models, small language models Organisation du cours – plan détaillé / Course organization - detailed outline: Session 1: AI Foundations and Business Landscape (3h) - Introduction to AI: History, current state, and business adoption trends - Overview of AI technologies and their business applications - Understanding the AI value chain and ecosystem dynamics Session 2: Hands-on Workshop: LLMs as a Junior Professionnal (3h) - Practical manipulation of Large Language Models - Real business scenarios and use cases - Prompt engineering and best practices - Individual exercises with immediate application Session 3: Creating Business Value with AI (3h) - AI business models and unit economics - Case studies of successful AI deployments - Methodology for successful AI implementation Session 4: Technical Foundations for Business Leaders (3h) - Understanding AI architectures: supervised/unsupervised learning, neural networks - The making of an LLM: training, fine-tuning, deployment - Beyond text: computer vision, voice, and multimodal AI - Technical implementation considerations for businesses Session 5: AI Governance and Organizational Transformation (3h) - Regulatory landscape: EU AI Act, industry-specific regulations - Ethics and responsible AI implementation - AI and ESG - Change management and skills transformation - Building AI-ready organizations Session 6: The Future of AI in Business (3h) - AI agents - Small Language Models - Reasoning Models - Multimodal Models Note: Agenda adjustments could be made prior to beginning of session Contenus ESG / ESG-related content (Environmental – Social – Governance): Environmental-r elated content Social-relat ed content Governance-re lated content 2. Moderate content 3. Significant content 3. Significant content Assessment Information: Pondération dans Outils / support / mode d’évaluation Durée et format la notation finale Tool/method of evaluation Duration Weight in the final grading Participation All along 40% 20 mn group Case Study Presentation 30% presentation Final exercise: AI critical thinking exercise 2 hours 30% Précisions complémentaires / Additional details: Updates to methods of evaluation could be made depending on number of enrolled students