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UvA en Scholen UvA en Scholen
Master
Vergelijk
Business Information Technology Management

The study programme

The Master’s Business Information Technology Management is an innovative, technology-driven Master's programme launching September 2025. This cutting-edge curriculum addresses the growing demand for professionals who can operate at the intersection of business strategy, information systems, and disruptive technologies such as AI, blockchain, and big data analytics.

The programme

The academic year is divided into 2 semesters, each with 3 periods. You complete each period with an examination. 

COURSES SEM 1 SEM 2 SEMESTER 1 SEMESTER 2 EC
  • Theories of Business Information Technology Management
    6

    This course covers data requirements analysis, machine learning, reinforcement learning, and big data. Students explore theories and applications using modelling, visualisation, and analytics tools. They gain hands-on experience with RapidMiner for predictive modelling and learn to assess model quality effectively.

  • Digital Transformation
    6

    This course aims to equip students with the skills to analyse organisational and management aspects of digital transformation. Through case studies, students explore digital migration, learning how firms adopt technologies and redesign business models to create and capture value effectively.

  • Data Science and AI for Business
    6

    This course covers large-scale data analysis and modelling, machine learning, deep learning, reinforcement learning, and big data. Through lectures and case studies, students learn to build predictive models using RapidMiner and assess model quality, applicable to structured and unstructured business data.

  • Change Management and Consultancy
    6

    This course explores change management theory and practice, focusing on digital innovations and Information Systems initiatives. It emphasises the consultant’s role, key instruments, and skills, adopting an organisational behaviour perspective with insights from agile approaches and mixed methodologies.

  • Ethics and Law
    3

    This course provides a thorough understanding of ethical and legal dilemmas in data use, algorithms, and AI. It covers EU data protection (privacy) laws and forthcoming AI legislation, examining regulatory efforts to address these challenges.

  • Thesis Clinic
    3

    Pressure-cooker workshop supporting the development of a strong research proposal. Given the innovative and quickly evolving nature of the field (with limited availability of established theories) an emphasis is put on innovative research approaches from fields such as design science.

  • Digital Impact Lab
    6

    This intensive, hands-on course resembles an extended hackathon, where students develop and test proof-of-concept applications using AI and low-code tools. Through agile methods, entrepreneurship, and sustainability concepts, they create impactful solutions in collaboration with external companies, fostering creativity.

  • Cyber Security and IT/AI Auditing
    6

    This course focuses on measuring, assessing, and managing cyber risks in an increasingly hyper connected world. It explores vulnerabilities in AI and IT applications, equipping students with the language of auditing and technology to engage with security leaders and understand business impacts.

  • AI Impact Lab
    6

    This course builds on the Digital Impact Lab, using the same methods and format but adding extra space to more fully develop impactful solutions based on available AI modules that can be 'mashed' into fully-fledged solutions.

  • Master’s Thesis Business Information Technology Management
    12

    The Master’s thesis is the final requirement for your graduation. It is your chance to dive deep into a topic that you are enthusiastic about. A professor in your field of choice (track) will supervise and support you in writing your thesis.

Send me the course schedule + programme summary

Honours programmes

Highly motivated students can participate in the Honours programmes Sustainability or Data Driven Management. These challenging programmes are a great chance to stand out for future employers.

Real-life case: Tackling student housing with AI

Finding affordable student housing in Amsterdam is a challenge. In the AI/Digital Impact Lab, students can take on a project to develop a proof-of-concept web application that addresses student housing shortages. Their platform gathers real estate data, predicts rent prices, and matches students with compatible roommates. Using machine learning and data analysis, they create a smart tool that considers affordability, transport links, and student preferences. In the next phase, AI-driven features—predictive rent trends, natural language processing for property reviews, and fraud detection—enhance the platform. Can AI make student housing more accessible and efficient?

What can students expect in class?

My approach to teaching change management and consultancy is rooted in practical application. I challenge students to think critically about organisational dynamics in the context of digital transformation. Prof. dr. Jeroen de Mast
Dr Chintan Amrit
In the Data Science & AI for Business course, the students will learn Data Science theory through lectures and explore the application of the algorithms through case studies using dedicated tools for modelling and visualisation, eventually creating analytics dashboards. Dr Chintan Amrit
Dr. Guido van Capelleveen
My teaching style in the Digital Impact Lab is highly collaborative and project-based. I push students to develop innovative solutions using the latest AI and low-code tools. Dr. Guido van Capelleveen
Frequently asked questions