Degree level and field of study

Master’s degree (EQF 7), Engineering, manufacturing and construction

Starting group code

​YTI20S1

Forms of study

Part-time studies

Structure of studies

Individual courses

Intended competence

Contact information

Rantonen Mika

Rantonen Mika

Lehtori, Senior Lecturer
IT, Institute of Information Technology
Teknologia, School of Technology
+358407167269

Key learning outcomes

Student knowledge profile is dictated through his personal learning plan.

Artificial Intelligence and Data Analytics Master’s Degree programme student knows how about possibilities of data analytics and artificial intelligence, their applications, the importance of data quality, and the ethics of artificial intelligence. The student will know how to plan, develop, implement data analytics and artificial intelligence to the various real-world challenges of the project. The student have knowledge and skills to apply the methods to right data in real environments.

The student will have the ability for life-long learning professionally, make decisions and communicate effectively as part of a multinational team. The student knows how to conduct research ethically.

Education content and professional growth and know-how

The professional growth of students is carried out with a tutoring process which starts at the very beginning of the studies and continues until graduation. In this process students complete their personal learning plans and discuss their needs for developing their target competences with their designated teacher tutors. The 60-ECTS programme is designed as obligatory core studies and optional studies. The discussions with the teacher tutor lead to selecting appropriate courses in students’ optional studies. The core studies icnludes 20 ECTS Artificial Intelligence and Data Analytics module and 30 ECTS Master thesis. Artificial Intelligence and Data Analytics module develop students' expertise in the Artificial Intelligence and Data Analytics field and the students can choose their topics for their 30-ECTS master thesis. The students are provided with personal supervision and guidance in master thesis seminars when writing their theses. The courses in the management module and the research and development module aim to develop students' shared master competences. In addition, students can take 5 ECTS of elective studies from management electives or other available master level courses and develop their complementary competence.

Flexible studies

Students have a choice of alternative or elective studies offered by partner universities, such as other universities of applied sciences (CampusOnline), universities and educational institutions involved in the EduFutura collaboration (University of Jyväskylä and Gradia). Higher level studies completed elsewhere may be accredited as part of your degree. The student must have a certificate or some other document to prove that they have completed the studies. Skills acquired elsewhere can also be described and demonstrated to enable accreditation. Further information is available in the Study Guide.

Working life oriented learning

Working life cooperation is an ongoing practice in the programme's curriculum as part-time students continuously reflect on their learning in the courses in the light of their current and previous experiences with their work experiences. Interaction with organisations is intensified during the master thesis stage in the studies when students target to develop practices at their work places or other organisations. Guest lectures given by industry professionals further enhance the working life cooperation.

The development assignments included in the study modules and courses are integrated with working life. The studies make use of the competencies and expertise of the study group members.

Career opportunities and employment

The students are able to carry out duties as data scientists, AI/ML specialists and managerial work in demanding artificial intelligence and data analytics projects. Developing as an AI/DA expert opens new and challenging positions, and an opportunity to progress in one’s career. The student will deepen his leadership and communication skills as well as networking skills in different roles in AI/DA projects and various roles within the organization. A postgraduate can work as an organizational developer and active producer of new knowledge and skills.

Degree-related qualifications

There are no specific degree-related or statutory qualification requirements in the field.

Further studies

The graduate may apply to continue on to postgraduate studies in science or arts at universities (Act 558/2009, Section 37). Studies can be continued by applying for corresponding post-degree education at universities abroad, for example. A university of applied sciences also provides opportunities for continuing education in the form of specialisation studies, open studies, an online study portal (CampusOnline) and working life based continuing education.

Education planning

The learning outcomes laid down in the curriculum of the degree programme have been derived from the analysis of the operating environment, JAMK's own strategy, and the school's core competence areas. The planning has been carried out in cooperation with representatives from regional working life. The development proposals and course feedback submitted by the students of the degree programme have been considered in the development of the curriculum. International expertise takes place by comparing the contents of the educational offerings of partner universities and with the expertise of the visiting lecturers. Representatives of the degree programme are closely involved in the activities of regional and international industirial networks.