MBA & AI Track

MODULE 1 - ENVIRONMENT AND GLOBAL MARKETS

Current socio-economic context

• Economic environment
• Financial System and markets
• Fiscal and Legal
• Legal tendencies
• Sustainability and environment

Marketing and commercialization in an international environment

• Marketing strategies
• Communication
• Digital Marketing and E-Commerce
• Sales Management

Intellectual Capital and Talent Management

• Human Capital Management
• Cross-Cultural Management
• Diversity and Inclusion
• Change Management

MODULE 2 - ORGANIZATIONAL STRATEGY

Business Strategy

• Human Capital Management
• Cross cultural management
• Diversity and inclusion
• Change management

Finance For Decision-Making

• Financial Planning and Control
• Budget Management
• Financial Decisions
• Investments Decisions
• Financial Markets and Startup Ecosystems
• Mergers and Acquisitions
• Business Intelligence

Entrepreneurship and Internationalization

• Digital Business & Innovation
• Agile Project Management - PRINCE2 and SCRUM
• Growth Hacking
• Design Thinking
• Internationalization Strategy Analysis
• International Market

MODULE 3 - STRATEGIC MANAGEMENT

Analytics from the Customer Perspective

• Socioeconomic Context for Big Data
• Business Strategy and Big Data
• Big Data Infrastructures and Component in the Context of Business
• From Big Data to Business Analytics
• Technology Map and Systems
• Data Strategy and Data Análisis
• Reporting and Dashboards
• Google Analytics

Transforming and Competing from an Operations Perspective

• Descriptive, Predictive and Prescriptive Analytics
• Transforming the Supply Chain
• Robotics and Process Automation
• Artificial Intelligence for Operations
• Demand Forecasting
• Business Intelligence

TRACK - Artificial Intelligence & Machine Learning

Sessions

• Introduction to the AI & Machine Learning module

• Transformation implementing Artificial Intelligence

• Smart products and services

• Ethics in AI

• Customer Experience & Customer Journey

• Smart interaction

• Neural network design

• Training neural networks

• Pre-trained models and transfer learning

• Keras, TensorFlow and PyTorch

Bootcamp

• Week 1 In-depth exploration
  • Text normalization and syntactic dependency analysis
  • Recurrent neural networks and transformers
  • Dataset repositories and pre-trained model such as HuggingFace
  • Generative models
  • Image classification
• Week 2 AI Applications and advanced use cases

MASTER'S THESIS

It’s not just the research paper that you need to complete your Master’s degree — it’s the right time and the right place for you to combine your academic experience with your professional ambition, personal vision and your creativity. It’s your chance to put everything you’ve been learning into practice and to work in order to get to where you want to be.