In this minor the art of communication meets the science of data. The minor is designed for the next generation of ‘Data Translators’ - visionary leaders who bridge diverse fields with the technological frontier of AI and Data Science.

In this minor, BUas students from other programmes than ADS&AI collaborate with ADS&AI students to find real-world solutions to problems in the industry you study using data and artificial intelligence applications. The ADS&AI students will serve as the technological experts and you and the other students on your programme will serve as the domain experts. You will work together to analyse the problem, assess past solutions, identify the necessary data, develop a solution and present the outcomes to your client.

Examples of potential projects are:

• Diminishing the returns of web shops by designing smarter recommender systems;
• Finding smart solutions for last-mile distribution;
• Using generative AI in game production;
• The use of robotics in hospitality;
• Increasing adertising revenue in the media by using data in content development;
• Energy saving by analysing data in smart buildings;
• The use of data to improve the impact of social media campaigns.

This minor will take you on a transformative journey where communication meets data science. Designed for students poised to become the next generation of ‘data translators’, this programme will prepare you to be a visionary leader who can bridge diverse fields with the technological frontier of artificial intelligence and data science.

As a participant, you will:

• Engage in cross-disciplinary collaboration. Unite with ADS&AI technologists to solve real-world industry problems using your domain expertise.
• Develop as a domain translator. Learn to articulate complex industry problems in a data-centric language that AI experts can understand and build on.
• Innovate with impact. Generate cutting-edge solutions by synthesising past approaches, current data insights and AI applications to elevate your field.
• Deliver transformational solutions. Create and present revolutionary, data-driven outcomes to industry clients to steer your sector towards a smarter, more efficient future.

Through hands-on projects, you will contribute domain knowledge and become fluent in strategies involving data analysis and AI application. This minor is not just about finding answers – it is about pioneering them.

• Studying on a programme that is also taught at BUas
• Propaedeutic certificate obtained

Present in digital learning environment

The ADS&AI programme takes a project-based approach, supported by an extensive digital learning environment. Students use this environment to acquire the necessary knowledge and skills. During lab days, students work in groups of approximately 5, on a real-life project for a real-life client, under the supervision of experienced staff.

Assessment: Their individual contribution to the project is recorded in a work log and a learning log. This contribution will be assessed using a rubric presented at the beginning of the project.

Language of instruction
English

Topics and Structure of the minor
Foundations of Artificial Intelligence:
>         A comprehensive introduction to the concepts, history and applications of AI.
>         Exploration of various AI disciplines: Machine learning, deep learning, neural networks, natural language processing (NLP) and robotics.

Ethics, Law and Data Governance:
>         In-depth discussion of data privacy, intellectual property and legal frameworks.
>         Ethical considerations in AI, including bias, fairness, transparency, and accountability.
>         Global and regional data protection regulations (e.g. GDPR and HIPAA) are also covered.

Research methods and problem-solving:
>         Strategies for identifying research questions in AI and data science.
>         Qualitative and quantitative research methods.
>         Problem-solving frameworks and critical thinking skills for ‘wicked problems’.

Communication and data storytelling:
>         Techniques for effective data visualisation and presentation.
>         The art of storytelling with data to influence decision-making.
>         Communication skills tailored for diverse audiences, including technical and non-technical stakeholders.

Driving change in organisations:
>         Theories and models of change management in the context of technological innovation.
>         Case studies on organisational adaptation to AI-driven workflows.
>         Strategies for overcoming resistance and managing stakeholder expectations.

Project management in tech-driven environments:
>         The fundamentals of project management: planning, execution, monitoring and closure.
>         Agile methodologies and their application in AI projects.
>         Collaboration tools and techniques for managing interdisciplinary teams.


Additional costs
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