Advanced AI and machine learning

In-depth understanding and utilisation of machine learning and artificial intelligence in different business areas requires knowledge of both the business area and the specific methods developed for it.

Machine learning and artificial intelligence methods have been developed for various industries, such as medicine, speech processing, speech recognition, machine vision and energy technology applications.

During the advanced AI courses of FITech universities, you will be familiarised with concepts such as data gathering, data preprocessing and normalisation, missing data and outliers.

Courses run through different aspects of modern intelligent methods for data processing. Some of the courses focus especially on classifiers and classification.

Courses present the concept of “big data” and different phenomena related to it, including requirements and principles for data. Courses also provide an elementary hands-on introduction to deep learning.

NB! Some courses have limits on the amount of FITech students. Persons without a valid study right to a Finnish university have preference to those courses.

Advanced AI and machine learning courses:

= Contact learning
= Online learning
= Blended learning (online & contact learning)
University of Oulu: Towards data mining (521156S), 5 ECTS. 2.9.–25.10.2019.

Max amount of FITech students: 30.

Prerequisites: Basics of statistical mathematics.

Amount and quality of data plays a major role in modern machine learning applications. In this course the students are familiarised with different concepts concerning data such as: data gathering, data preprocessing and normalisation, combining data from multiple sources, missing data and outliers.

After this course the student has good capabilities to identify use cases for data that has been gathered in industrial environment or organise high-quality data gathering for new applications.

More info >>

Responsible teacher: Satu Tamminen (satu.tamminen(at)oulu.fi)

 

University of Oulu: Deep learning (521152S), 5 ECTS. 28.10.–20.12.2019.

Max amount of FITech students: 30

Prerequisites: BSc in Computer science or equivalent.

This course provides an elementary hands-on introduction to deep learning. Students taking this course will learn the theories, models, algorithms, implementation and recent progress of deep learning and obtain empirical experience on training deep neural networks. Applications of deep learning to typical computer vision problems such as object detection and segmentation will also be included.

Coursework will consist of programming assignments in TensorFlow. After this course, students will learn to implement, train and debug their own neural networks.

More info >>

Responsible teacher: Li Liu (li.liu(at)oulu.fi)

University of Oulu: Artificial intelligence (521495A), 5 ECTS. 6.1.–6.3.2020.

Max amount of FITech students: 30.

Prerequisites: BSc in Computer science or equivalent.

Artificial intelligence course runs through different aspects of modern intelligent methods for data processing. Course topics include among others intelligent agents, search strategies, reinforcement learning and machine learning from observations.

This course gives the student acquirements to start designing various types of artificial intelligence based solutions for real life problems.

More info >>

Responsible teacher: Abdenour Hadid (abdenour.hadid(at)oulu.fi)

University of Oulu: Machine learning (521289S), 5 ECTS. 6.1.–6.3.2020.

Max amount of FITech students: 30

Prerequisites: BSc in Computer science or equivalent.

On this course, the focus is especially on classifiers and classification. Other topics covered include statistical regression, Bayesian decision theory and feature extraction.

After completing this course the student is able to design basic classifiers for different classification tasks as well as assess the performance of these classifiers.

More info >>

Responsible teacher: Tapio Seppänen (tapio.seppanen(at)oulu.fi)

University of Oulu: Big data processing and applications (521283S), 5 ECTS. 9.3.–8.5.2020.

Max amount of FITech students: 30

Prerequisites: BSc in Computer science or equivalent.

During this course, the student gets familiar with the concept of “big data” and different phenomena related to it, including requirements and principles for data intensive systems and their implementation as well as benefits, risks and restrictions of available big data solutions.

After the course the student can identify real life cases where big data solutions are needed and design basic solutions to big data problems.

More info >>

Responsible teacher: Ekaterina Gilman (ekaterina.gilman(at)oulu.fi)

Further information

University of Oulu

Coordinator: Riku Hietaniemi (riku.hietaniemi(at)oulu.fi)

Type of study unit

Set of courses

Teaching semester

2019–2020

Host university

University of Oulu

Open for degree student

Yes

Open for non-student

Yes

Level of studies

Advanced

Teaching methods

Contact learning or online learning

Place of contact learning

Oulu

Language

English

Go back to all Courses & Programs

Go back