Real-World Impact of AI Applications
The Real-World Impact of AI Applications is a study module in the Data, Analytics, and AI for Professionals (DAAP) program and can also be taken as a stand-alone program.
Artificial intelligence is increasingly shaping the world around us — from the way decisions are made to how systems are developed, governed, and maintained.
The Real-World Impact of AI Applications provides a comprehensive exploration of the societal impact of AI, equipping participants with the knowledge and critical perspective needed to navigate the ethical, legal, and technical challenges of AI in practice.
You will examine how AI systems interact with the real world, delving into topics such as data privacy, ethics, security, sustainability, and regulatory frameworks like the EU AI Act. The module also covers the responsible use of open data and open-source code, as well as the continuous development and lifecycle management of AI systems. Throughout the program, case examples, group discussions, and expert insights offer a grounded understanding of how to build AI solutions that are secure, ethical, and aligned with societal values.
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Benefits
As AI systems increasingly influence society, organizations must ensure their use is ethical, secure, and aligned with evolving regulations. This module equips professionals with the insight to navigate the ethical, legal, and practical challenges of AI — enabling organizations to make responsible, compliant, and future-ready decisions in the development and deployment of AI technologies.
For
The program is suitable for anyone who needs deep understanding and skills to apply data analytics and AI technology.
The program is well-suited, for example, for
- IT specialists, Managers, and Directors
- Analysts
- Business Development Leaders and Managers
- HR professionals
- Product Managers
- Cloud Engineers
- Programmers and Developers
- Engineers from different fields
Instructors
Laura Ruotsalainen
Laura Ruotsalainen is an Associate Professor of Spatiotemporal Data Analysis for Sustainability Science at the Department of Computer Science at the University of Helsinki.
Her current research interests include the development of computer vision, estimation and machine learning algorithms for creating and using accurate and reliable spatiotemporal data, namely navigation data, especially for the development of autonomous systems enabling sustainable smart cities. For years, she has been teaching courses and supervising research on navigation at the Aalto University and the University of Helsinki and more recently also a course on Computer Vision at the University of Helsinki.
Jukka K. Nurminen
Jukka K. Nurminen is a Professor of Computer Science at the University of Helsinki.
He has worked extensively on software research in the telecom industry at Nokia Research Center, in academia at Aalto University, and in applied research at VTT. His key research contributions are on energy-efficient software, mobile peer-to-peer networking, and cloud solutions but his experience ranges widely from applied optimization to AI, from network planning tools to mobile apps, and from software project management to tens of patented inventions. He received his MSc degree in 1986 and PhD degree in 2003 from Helsinki University of Technology (now Aalto University) in applied mathematics. Currently, his main interests are in the engineering of machine learning systems, fair and reliable operation of AI, and software development for quantum computers.
Program Fee and Registration
Other Data, Analytics, and AI for Professionals (DAAP) Modules
You can register for individual stand-alone Data, Analytics, and AI for Professionals modules or take the complete Data, Analytics, and AI for Professionals program, including all four modules.
