A national initiative on education and competence in Artificial Intelligence

Courses

Competence development is becoming increasingly important for the industry. Our goal is to ensure that companies and individuals have the education required to succeed in the AI-driven future. The following courses are intended to cover the areas demanded by employees in the business and private sectors when it comes to AI. The courses offered vary in length from single days to several weeks. Use the filtering function below to find the education that suits you!

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Online

The rapid development of digital technologies and advances in communications have led to gigantic amounts of data with complex structures called ‘Big data’ being produced every day at exponential growth. The aim of this on-line course is to give the student insights in fundamental concepts of machine learning with big data as well as recent research trends in the domain. The student will learn about problems and industrial challenges through domain-based case studies. Furthermore, the student will learn to use tools to develop systems using machine-learning algorithms in big data. This course is possible to combine with a full-time employment.

Read more at Mälardalen University

Örebro

The course offers knowledge of the basic concepts with machine learning, the selection and application of different machine learning algorithms as well as evaluation of the performance of these learning systems. After completing the course, student should be able to prepare data and apply machine learning techniques to solve a problem in an intelligent system.

Read more at ÖREBRO UNIVERSITY

Örebro

This course looks into different phenomena of human interaction with mixed reality. We will examine different aspects of human perception of mixed reality, depending on such factors as fidelity, immersion, and presence. In the course we look at the way people act when being immersed into virtual or remote environment. And we look at the methods of building efficient interaction scenarios and measuring interaction quality, using qualitative and quantitative tools. Upon completion of this course, students will be able to apply theoretical knowledge on developing mixed reality experiences to appropriate industrial problems and evaluate the effect of mixed reality in a critical manner.

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Örebro

The course addresses the major principles in logic and constraint programming. The main focus of the course is on Stable Model or Answer Set semantics. This course  also focuses on formalizing and solving various problems within a declarative paradigm. After completing the course, the student will be able to apply a suitable symbolic reasoning method based on answer set solvers to solve a problem within an intelligent system.

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Örebro

The course addresses the basic concepts within classical artificial intelligence (other than machine learning). Traditional artificial intelligence is characterized by the so-called declarative approach to problem solving. The course deals with a selection of different intelligent problem-solving methods, both in theory and practice. After completing the course, the student will be able to model and use appropriate generic solution algorithms to solve problems in an intelligent system.

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Örebro

The course covers three specialist fields of knowledge within AI: planning of resources, robot motion planning and multi-robot coordination, as well as introduce the specific principles behind these subjects, namely systematic and sampling-based searching algorithms, constraint-based reasoning and robot kinematics. Within each subject (planning of resources, robot motion planning and multi-robot coordination), a state-of-the-art tool will be presented and used as the basis for a project work.

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Örebro

The course offers knowledge on Robot Operating System (ROS), how it works and how it is applied within a variety of artificial intelligence and robotics areas. You will use ROS to design parts of an intelligent system and test these both in simulation as well as on existing robot platforms.

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Online

This on-line course will teach you how to build convolutional neural networks. You will learn to design intelligent systems using deep learning for classification, annotation, and object recognition. This course is possible to combine with a full-time employment.

Read more at Mälardalen University

Online

The on-line course will give insights in fundamental concepts of machine learning and actionable forecasting using predictive analytics. It will cover the key concepts to extract useful information and knowledge from big data sets for analytical modelling. This course is possible to combine with a full-time employment.

Read more at Mälardalen University
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