Strategic management
Frameworks for analysing competitive environments and building sustainable advantage in digital markets — industry analysis, resource-based views, strategic positioning.
18 courses across four semesters, organised around four pillars and a research track. Each carries 6 ECTS — except the final dissertation, which is 18.
Frameworks for analysing competitive environments and building sustainable advantage in digital markets — industry analysis, resource-based views, strategic positioning.
Economic principles applied to business decision-making — demand, pricing, cost optimisation, market structures, and game theory in digital markets.
Mapping, modelling, and optimising business processes with BPMN and lean methodologies — you'll design automated workflows in real organisational contexts.
Psychological and sociological foundations of consumer decision-making in digital environments — behavioural economics, nudge theory, data-driven segmentation.
Introduction to academic research methodology — literature review techniques, quantitative and qualitative design, first formulation of dissertation topics.
How information asymmetry, network effects, and data economics shape modern markets — platform economics, attention models, data as a strategic asset.
The legal and regulatory landscape shaping AI in business — the EU AI Act, data protection and GDPR, algorithmic accountability, liability, IP in machine-generated work, and building compliant AI products.
Financial analysis, valuation, capital budgeting, and risk management for technology ventures — you'll build models and evaluate investment decisions in high-growth digital businesses.
Foundations of AI with a business lens — supervised and unsupervised learning, NLP, computer vision, and how to take an AI strategy from proof of concept to production.
From ideation to launch — lean startup, business model canvas, customer discovery, MVP development, and pitching to FABIZ's VC partners on real venture concepts.
How established companies reinvent themselves — change management frameworks, digital maturity models, cultural transformation, case studies from enterprises navigating disruption.
Structured approaches to generating and implementing innovation — design sprints, innovation accounting, portfolio bets, and building innovation culture inside organisations.
Hands-on ML for business applications — regression, classification, clustering, neural networks, and model evaluation on real datasets focused on extracting business value.
Business applications of IoT and distributed ledger — smart contracts, supply chain traceability, connected devices, edge computing, building viable products on emerging tech.
End-to-end product lifecycle — user research, prototyping, roadmapping, AARRR and North Star metrics, stakeholder management, building products users actually want.
Enterprise BI architectures, data warehousing, ETL pipelines, and dashboarding — you'll build end-to-end analytics solutions and translate raw data into strategic decisions.
Planning and executing digital communication campaigns — content strategy, paid media optimisation, social analytics, influencer marketing, ROI measurement.
The capstone of MDBI — you'll complete your master's dissertation under faculty supervision, applying research methodology to a real problem in digital business, with a public defence.