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Data, Analytics, and AI for Professionals Program 

In-depth understanding and practical skills in data analytics and artificial intelligence technologies

Is your job to advance data utilization in your organization? Are you selecting the appropriate tools and technologies for your organization to utilize data and artificial intelligence? What are the current AI technologies, and how can they be developed and deployed?

The Data, Analytics, and AI for Professionals (DAAP) program offers you possibilities for understanding and solving business opportunities and challenges related to AI as well as for utilizing and developing AI services. The training program has been designed to help organizations and individuals adopt – understand, select, use, apply, and develop – new technologies and tools.

We gathered together our best training programs and instructors focusing on data, analytics, and AI and created a program supporting life-wide learning and a flexible learning path.

The modular structure of the DAAP program allows participants to study interesting topics at their own pace. The whole program consists of three individual modules (each three days).

Contact Us

The program is offered in cooperation with the Finnish Center for Artificial Intelligence (FCAI).

Start

Introduction to AI and Data / Module 1

Flexible Learning

Introduction to AI and Data

Module 1 / 3 days

AI Methods and Applications

Module 2 / 3 days

Ethical and Juridical Implications

Module 3 / 3 days

 

Learning Objectives:

The DAAP program is taught by leading instructors and experts from Aalto University, the University of Helsinki, and the Finnish Center for Artificial Intelligence (FCAI) as well as from the most advanced companies in the field.

We have gathered together our comprehensive experience and the best trainers and content from our popular data, analytics, and AI programs such as the Diploma in Artificial Intelligence. The program combines the latest research knowledge and practical learning through different examples and practical assignments.

Build your personalized learning path and complete your studies at your own pace. We offer interesting modules that help you deepen your knowledge of AI. The module selection is updated continuously.

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

  • product managers;
  • development leaders and managers;
  • IT specialists, managers, and directors;
  • analysts;
  • cloud engineers;
  • programmers and developers; and
  • engineers from different fields.

Contents

The modules of the Data, Analytics and AI for Professionals program can be completed as standalone programs. You can study modules flexibly and complete the number of modules you need.

We offer three modules that each consist of three study days. The studies include both intensive contact teaching and learning by doing. The topics include data strategy, AI technologies, and applications as well as juridical questions related to data. The program includes practical examples.
 

Independent assignments and project work complement the studies and allow you to apply your learning in practice. Those completing all three modules have a chance to complete a project in which they get personalized assistance from our experts.

Schedule

The Data, Analytics, and AI for Professionals (DAAP) studies can be completed in about six months or over a longer period of time. Participants can complete all three modules or just the modules they need.

Instructors

Teemu Roos

Teemu Roos is a Professor at the Department of Computer Science, University of Helsinki.

Roos' research interests include the theory and applications of artificial intelligence, machine learning, and data science. He also teaches introductory courses on these topics with a total of up to 500 students annually. He has developed applications of AI in areas such as mobile computing, genomics, epidemiology, quantum physics, and digital humanities.

Teemu Roos received a Ph.D. in computer science from the University of Helsinki in 2007.

Henri Schildt

Henri Schildt is a tenured professor with a joint appointment at the Aalto University School of Business (Management & Organizations) and the School of Science’s Department of Industrial Engineering and Management.

His research interests span technology strategy, organizational change, and strategy process (with specific interest in reasoning under uncertainty and the use of data analytics). He is currently heading two research programmes on data-driven management and the management of digitalization in Finnish manufacturing companies. Henri Schildt completed his PhD at Helsinki University of Technology in 2007.

Jaakko Hollmén

Jaakko Hollmén is Chief Research Scientist at the School of Science and Technology at Aalto University. Hollmén’s research focuses on machine learning, data mining, and artificial intelligence. He has a special interest in predictive analytics.

Hollmén has more than 20 years experience in data analytics, both in manufacturing industry and university research. He is a founding member of Northlet Ltd., which offers analytics services and consulting for companies aiming to improve their usage of analytical tools. In 2017, Hollmén was a key organizer of ECML-PKDD 2017 – the biggest conference in machine learning and data mining in Europe.

Marko Turpeinen

Dr. Marko Turpeinen is an Adjunct Professor at Aalto University. He is also founder and CEO of a recently established data sharing company called 1001 Lakes.

He was previously the Finnish Node Director of EIT Digital, a Knowledge an Innovation Community of the European Institute of Innovation and Technology and Professor in Media Technology at The Royal Institute of Technology (KTH) in Stockholm. He has extensive industrial experience from the media industry, as between 1996 and 2005 he worked in various executive positions at Alma Media Corporation, a Finnish media company.

His current academic research addresses issues in customized media content, human-centric approach to personal data, and the role of AI and algorithmic power in networked society. He has a Doctor of Technology Degree in Computer Science from Helsinki University of Technology (now Aalto University) and a Master of Science Degree in Media Arts and Sciences from Massachusetts Institute of Technology (MIT).

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.

Antti Ukkonen

Antti Ukkonen is an Academy Research Fellow at the Department of Computer Science, University of Helsinki. He has 15 years of experience in research and development of data analysis algorithms.

Prior to joining UoH, Antti has worked as a data scientist at Yahoo! Research, Helsinki Institute for Information Technology HIIT, and Finnish Institute of Occupational Health. He has published over 40 scientific articles in international journals and conferences on the topics of data mining, machine learning, and algorithms. He obtained his doctoral degree from Helsinki University of Technology in 2008.

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