Aarhus University Seal

From Data to AI: Responsible Pathways

This course is cancelled

This course examines the dynamic interplay of data and AI, and provides a holistic view of how AI solutions can be deployed ethically, operationally, and strategically. 

Beginning with a comprehensive overview of the modern data ecosystem, the students learned about the essential elements of Data Governance. These include principles guiding this domain, the significance of a well-structured governance framework, and the ripple effects of AI-driven decision-making. Integrating innovation and accountability is one of the tenets of AI management. 

As the course delves more profoundly, it unravels strategies pivotal to AI Management. The course provides insights into the operational challenges faced by organizations in AI adoption. By engaging with real-world case studies, students gain firsthand knowledge of how to align AI projects with overarching business objectives, ensuring both feasibility and ethicality. The course then moves to the practicality of Responsible AI. This course emphasizes the importance of understanding and mitigating AI risks to ensure that AI deployments are devoid of inadvertent biases and societal repercussions.  

The latter modules venture into the realm of Explainable AI (XAI). Here, students are equipped with tools and techniques to elucidate AI decision-making processes, thus making these once-black-box algorithms understandable and trustworthy. This course accentuates the undeniable importance of XAI, especially in sectors where AI decisions directly impact human lives. Concluding the journey, the course emphasized AI Risk Mitigation. Best practices were showcased, equipping students to anticipate, identify, and manage potential pitfalls of AI applications. This culminates in a comprehensive understanding of building a proactive culture of AI safety and responsibility. 

By traversing these meticulously designed modules, students will gain a profound understanding of the theoretical constructs and pragmatic challenges of Data Governance and Responsible AI. They are sculpted into astute professionals capable of navigating the complexities of ethical AI deployment in any organizational milieu, championing transparency, fairness, and accountability.

Exam info and full course description

Exam info and full course description can be found in the course catalogue.

Admission Requirements

Course specific:

A Bachelor’s degree in Business Administration or Business Economics or an equivalent degree.  


Exchange Students: nomination from your home university

Freemovers: documentation for English Language proficiency

You can read more about the admission here.


Arif Perdana


Dr. Arif Perdana's diverse research illuminates the transformative role of digital technologies such as algorithmic systems, automated decision making, data analytics, and blockchain in a variety of sectors, from finance to education to healthcare transformation. He has provided critical insights into the challenges of adopting digital technologies while exploring technology-driven strategies across sectors. His current studies focus on responsible artificial intelligence (AI) in finance, the applicability of blockchain in business, and machine learning algorithms. These various studies illustrate his extensive portfolio and commitment to tackling the complexities of digital strategies.