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Artificial Intelligence for Executives

Home / Oferta Formativa / Coimbra Business School / Microcreditation / Micro-credential in Artificial Intelligence for Executives

Base Knowledge

Not applicable

Teaching Methodologies

The teaching methodology is oriented towards experiential and strategic learning, combining moments of interactive exposition, case discussion and application exercises.

The synchronous online sessions privilege the exchange of experiences between executives and the critical debate on the impacts of AI on business

Learning Results

This course is aimed at executives, managers and business decision-makers who want to understand the strategic impact of Artificial Intelligence (AI) on business and identify opportunities for organizational value creation.

The course provides an integrated view of key AI technologies and their business applications, covering topics such as automation, predictive analytics, generative AI, ethics, and digital transformation.

Participants will develop skills to assess the potential of AI in their organizations, lead technological innovation projects, and align AI adoption with corporate strategy.

Program

  1. Artificial Intelligence in Business Overview

Global trends, impact on the economy and application sectors.

  1. AI Fundamentals and Enterprise Data

Key concepts, machine learning, deep learning, and big data.

  1. Strategic applications of AI in functional areas

Marketing, operations, finance, human resources, and customer service.

  1. Generative AI and process automation

Case studies and emerging tools (ChatGPT, Copilot, Midjourney, Gemini).

  1. Data-driven decision-making and predictive models

Decision support tools and smart dashboards.

  1. Change management and digital leadership

Adoption strategies, organizational resistance, and culture of innovation.

  1. AI Ethics, Privacy and Regulation

Governance, transparency and responsible use of technology.

  1. Final project: proposal to integrate AI into a specific organization or sector.

Curricular Unit Teachers

Professor a definir - ISCAC

Grading Methods

Summative assessment
  • - Individual and/or Group Work - 80.0%
  • - Attendance and Participation - 20.0%

Internship(s)

NAO

Bibliography

  • Davenport, T. & Mittal, N. (2023). All-in on AI: How Smart Companies Win Big with Artificial Intelligence. Harvard Business Review Press.

  • McKinsey & Company (2022). The State of AI in 2022. McKinsey Global Institute.

  • Brynjolfsson, E. & McAfee, A. (2017). Machine, Platform, Crowd: Harnessing Our Digital Future. W. W. Norton.

  • Kotler, P., Kartajaya, H. & Setiawan, I. (2021). Marketing 5.0: Technology for Humanity. Wiley.

  • Daugherty, P. & Wilson, H. (2018). Human + Machine: Reimagining Work in the Age of AI. Harvard Business Review Press.

  • Ferrão, M. (2023). Inteligência Artificial Aplicada à Gestão. Edições Sílabo.

  • Recursos digitais: IBM Watson AI Business Hub, OpenAI Business Toolkit, Google Cloud AI for Business, BCG AI Executive Insights.