The Programa Dirección Data, Analytics & Inteligencia Artificial combines business strategy with data science to help you discover new business opportunities and learn how to create competitive advantages for your organization.
Its practical, case-study-based approach is designed to give you an in-depth understanding of the various applications of data in strategic decision-making. As a result, you’ll be able to implement truly effective digital transformation processes.
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MODULE 1: Fundamentals of Management
Acquire the tools necessary to understand the environmental context in which organizations operate, enabling you to identify and capitalize on new business opportunities.
- Strategic management
- Corporate finance
- Marketing
- Team management
- Negotiation
MODULE 2: Technological Foundations
This module prepares students to understand the data lifecycle, the key tools to consider and reference architectures. It also introduces trends and Edge Computing as the next step in managing complex systems: Quantum Computing, Extended Reality and Blockchain, the major revolution of the present and future in the development and applications of Artificial Intelligence.
- Business Strategy & Data Science
- Technological Components: Lifecycle
- Tools: Python, GitHub Notebook (intro)
- Reference architectures
- Edge Technologies: Quantum Computing/Blockchain/Extended Reality
MODULE 3: Sectors/Industries (Use Cases/Disruptive Business Models)
In this module, participants learn about opportunities in strategic information management through experiences and use cases, both sector-specific and cross-sector, in the business-to-consumer (b2c) and business-to-business (b2b) environments, identifying best practices in the application of artificial intelligence and data analytics to optimize or create new business models.
- Telcoms & utilities sector
- Financial sector
- Retail & distribution sector
- Agri-food sector
- Healthcare sector
- Services/infrastructure sector
MODULE 4: Tech LABS (12) - Hands-on
This module includes 12 DATA LABS, giving participants hands-on experience with innovative use cases: NLP, facial and voice recognition, search engines, transfer learning, 3D scenario development, process mining, generative AI, multimodal models, copilots and open LLMs.
LAB 1: MACHINE LEARNING I - FUNDAMENTALS - SUPERVISED AND UNSUPERVISED MODELS
LAB 2: MACHINE LEARNING II / ADVANCED MODELS + DEEP LEARNING - NEURAL NETWORKS
LAB 3: GENERATIVE AI I - OpenAI - ChatGPT - GPTs / OpenArt
LAB 4: GENERATIVE AI II - Multimodal Models / Microsoft Copilots
LAB 5: GENERATIVE AI III - Google / Gemini / NotebookLM
LAB 6: GENERATIVE AI IV - Open LLMs - LM Studio (Llama, Qwen, Gemma and DeepSeek)
LAB 7: AI Process Mining - Process Re-engineering - Celonis
LAB 8: AGENTIC AI I - AI Value Factory: Frameworks - Replit (functional) / Cursor (engineering) / Antigravity
LAB 9: AGENTIC AI II - Workflows / Simulators - End-to-End Applications - No Code / Low Code - n8n / Lovable
LAB 10: AGENTIC AI III - Multi-agent Orchestration - Reimagining the Enterprise by Functional Area - Stack AI / Asana (*)
LAB 11: AGENTIC AI IV - Innovation / Design Lab - Anthropic / Claude
LAB 12: AI Prototyping / UX-UI / Low Code - Figma
MODULE 5: STRATEGY LABS (2) - Hands-on
This module applies design techniques to solve complex business problems and generate strategic innovation, laying the groundwork for the final projects and capstone. Participants also work with three key tools for generating insights, dashboards and storytelling.
LAB 13: Design Thinking - Workshop
LAB 14: Augmented Analytics / Storytelling - Dashboards I - Tableau / Power BI
LAB 15: The AI Boardroom: Trustworthy AI & Critical Thinking - Parts I and II
Trustworthy AI - Critical Thinking: Challenging Recommendations / Verifying Evidence / Evaluation and Auditing - Part I
Trustworthy AI - Critical Thinking: The Human Dimension: Decision-maker Neuroscience / Biases / Self-awareness - Part II
MODULE 6: GOVERNANCE MODELS AND ORGANIZATIONAL IMPACT / METHODOLOGIES
This module presents an AI management and governance model and its components: access, quality, ownership and security. It also examines the new roles and the leadership needed to make the most of this digital transformation.
DATA GOVERNANCE / DATA-DRIVEN ORGANIZATIONS - INTERNATIONAL STANDARDS
MODEL GOVERNANCE / MLOPS / AGENT GOVERNANCE
LEADERSHIP / CULTURE / CHANGE MANAGEMENT - LEADING EXPERIENCES
MODULE 7: ENTREPRENEURSHIP/FINAL CAPSTONE PROJECT
Finally, students are trained in key performance indicators; best practices in ai/data projects are shared and teams are guided through the development of their initiatives and projects until their presentation to the evaluation committee.
- Startup life cycle: Entrepreneurship_talent_innovation
- Project faculty
- Project coaching
Frequently Asked Questions
How are the classes in the Programa Dirección Data, Analytics & Inteligencia Artificial structured?
The program is divided into seven modules:
- Module 1: Business Strategy & Fundamentals of Analytics/AI (MBA).
- Module 2: Technological Foundations.
- Module 3: Sectors/Industries (Use Cases/Disruptive Business Models).
- Module 4: Tech Labs; hands-on.
- Module 5: Strategy Labs; hands-on.
- Module 6: Governance/Organization/Leadership/Methodologies.
- Module 7: Final Capstone Project.
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