Basics of Artificial Intelligence – AI as a Business Driver
Artificial intelligence will rapidly change the world, creating new opportunities and needs for completely new kinds of solutions. The current discussion is focused on future prospects and threats, but what, in actual fact, is AI and what can we achieve with it? And what can we expect from the future?
Basics of Artificial Intelligence is a two-day training program, which provides a practical and comprehensive overview of artificial intelligence, various technologies and their impact on business, human beings and society. Led by leading researchers in the field, the program focuses on issues such as the applications of artificial intelligence, the prerequisites for its implementation, and the strengths of people and AI.
The training program is implemented in cooperation with the Finnish Center for Artificial Intelligence (FCAI).
Note that this program is held in Finnish.
After the program, you will understand what artificial intelligence is and how it will affect business. You will gain an up-to-date picture of the different technologies and their development phases.
The program is intended for senior executives and business developers.
Basics of Artificial Intelligence program is suitable for CEOs, senior business managers and development managers.
Contents and Schedule
The Basics of Artificial Intelligence program consists of two intensive training days held in Aalto EE's premises in Helsinki.
The program days consist of contact teaching, case presentations of companies applying the related technologies, and ‘thinaskprints’, in which the issues learned are applied to the activities of your organization.
Dr. Samuel Kaski is an Academy Professor at the Department of Computer Science at Aalto University and Director of the Finnish Center for Artificial Intelligence (FCAI).
Previously Dr. Kaski has been the director the Finnish Centre of Excellence in Computational Inference Research COIN and Helsinki Institute for Information Technology HIIT. His primary research interests are probabilistic machine learning methods and their multidisciplinary applications.
Arto Klami is Assistant Professor of Computer Science and Academy Research Fellow at University of Helsinki, where he leads the Multi-Source Probabilistic Inference research group. He is also member of Helsinki Institute for Information Technology HIIT and Finnish Center for Artificial Intelligence.
He received his PhD in computer science from Aalto University in 2008. Arto has more than 15 years of experience in artificial intelligence and machine learning research, and he has published more than 50 scientific articles in the field. His primary research interests are in statistical machine learning, data integration and probabilistic programming, and he has worked on wide range of applications from computational biology and neuroscience to human-computer interaction and analysis of heterogeneous traces of human activity.
Tutkija, Helsingin yliopisto
Katri Saarikivi works as a researcher at University of Helsinki. She is a cognitive neuroscientist, researcher, team leader and co-founder of the NEMO project (Natural Emotionality in Digital Interaction), which won the grand-prize in the science-based idea competition, Helsinki Challenge.
In her research, she explores the neural mechanisms behind empathy and fruitful interaction, particularly in digital environments. She is fascinated by social cognition, cognitive control, and how these functions emerge from the brain processes.
As an independent consultant and speaker, Saarikivi works with organizations on subjects like the future of work, digital work, connectivity, creativity, and human-centeredness. She hopes to bring relevant neuroscientific knowledge to organizations to support human interaction and learning, and thereby better value-creation.
Katri Saarikivi holds a Master’s in Psychology from the University of Helsinki.
Eeva Vilkkumaa on apulaisprofessori Aalto-yliopiston kauppakorkeakoulun johtamisen laitoksella.
Tutkimuksissaan hän on keskittynyt matemaattisten mallien kehittämiseen yritysten ja julkishallinnon päätöksenteon ja resurssien allokoinnin tueksi.