Master’s Degree Programme in Data Expertise and Artificial Intelligence: 22YDS
Code: 22YDS
Master of Health Care
Master of Health Care
Master of Health Care
Master of Health Care
Master of Health Care
Master of Health Care
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Description
ELIGIBILITY
Master's degree is designed for people who have completed a Bachelor’s degree, and who have at least two years of work experience in a relevant field after graduation. In cases of persons who have completed a vocational degree or have another university degree, and who have since completed an applicable Bachelor’s degree, relevant work experience may be accepted from the time before graduation from said degree programme.
COMPETENCES
Digitalization is changing society and organizations rapidly. As a result, the needs of working life are also changing. The importance of data is constantly growing and artificial intelligence is increasingly being used in various applications. These changes brought about by digitalization require experts in various fields to increase their knowledge of the data and identify the potential of artificial intelligence, without forgetting the ethical aspects involved.
The Master’s Degree Programme in Data Expertise and Artificial Intelligence programs will equip you with the ability to independently act as an expert and developer in demanding tasks that require data and utilize artificial intelligence or are intended to be utilized in the future. During the training, you will learn to recognize the different data needs of your specialist area and understand the potential of utilizing data in your expertice area. You will also learn how to pre-process, analyze and visualize data in practice.
During the training you will familiarize yourself with the concepts and methods of artificial intelligence and you will also apply the methods and applications of artificial intelligence in practice. Participating students come from a variety of educational backgrounds (including engineers, nurses, and tradenomes), which gives you an excellent opportunity to network and understand the concepts of experts in different disciplines and ways to solve problems. The aim is for students to share knowledge and skills with each other. Training will equip you to deepen your professional skills and provide you with methods and tools to continue developing your skills beyond training.
PROFESSIONAL STATUS
Companies and organizations are in dire need of experts who have not only their own substantive knowledge but also data and artificial intelligence expertise. They can work as experts in a variety of project, design and development tasks.
Job titles can include a senior engineer, a data expert, an application specialist, a project manager, a system manager, a special engineer, or a specialist.
EDUCATION VALUE BASIS
Responsibility and ethics are always associated with data processing and the use of artificial intelligence. These are also suitable as a value basis for education.
STRUCTURE
The studies consist of a thesis (30 ECTS) research and development related to data and / or artificial intelligence and advanced professional studies (25 ECTS credits), free-choise studies (15 ECTS), optional elective studies (20 ECTS credits, depending on the student background).
In advanced professional studies, you will develop your knowledge and skills in digitalisation, data skills and artificial intelligence techniques.
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Show study timings by academic year, semester or period
| Code | Name | Credits (cr) | 2021-2022 | 2022-2023 | Spring 2022 | Autumn 2022 | Spring 2023 | 3. / 2022 | 4. / 2022 | 1. / 2022 | 2. / 2022 | 3. / 2023 | 4. / 2023 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 22YDS-1001 |
Advanced Professional Studies
(Choose all ) |
25 | |||||||||||
| 5Y00FD85 | Digitalisation Technologies | 5 | 5 | 5 | 2.5 | 2.5 | |||||||
| 5Y00FD86 | Data Collection and Processing | 5 | 5 | 5 | 2.5 | 2.5 | |||||||
| 5Y00FD88 | Data Analysis and Data Visualization | 5 | 5 | 5 | 2.5 | 2.5 | |||||||
| 5Y00FD89 | AI Solutions | 5 | 5 | 5 | 2.5 | 2.5 | |||||||
| 5Y00FD87 | AI Methods | 5 | 5 | 5 | 2.5 | 2.5 | |||||||
| 22YDS-1002 |
Common Master Studies
(Choose ects: 15) |
15 | |||||||||||
| NY00EC51 | Evidence-Based Practice | 5 | |||||||||||
| NY00EC53 | Quantitative Research Methods, Effectiveness (incl. SPSS) | 5 | |||||||||||
| NY00EC55 | Qualitative and Action-based Research and Development Methods | 5 | |||||||||||
| NY00EC57 | Future Research, Foresight and Innovation | 5 | |||||||||||
| NY00EC59 | Leadership and HRM | 5 | |||||||||||
| NY00EK73 | Knowledge Management | 5 | |||||||||||
| NY00FD95 | Analyzing management communication | 5 | |||||||||||
| NY00EC67 | Project Competence | 5 | |||||||||||
| NY00EK08 | The Development of Activities through Service Design | 5 | |||||||||||
| NY00EC61 | Foundations of Financial Management | 5 | |||||||||||
| NY00EK72 | Strategic Financial Management | 5 | |||||||||||
| NY00EC63 | Strategy and Change Management, as well as Communication | 5 | |||||||||||
| NY00EK75 | Acquiring Customers in Digital Channels | 5 | |||||||||||
| NY00EK74 | Experience Design | 5 | |||||||||||
| 7Y00FK31 | Working in a Project | 5 | |||||||||||
| 22YDS-1003 |
Free-Choice Studies
(Choose ects: 20) |
20 | |||||||||||
| 5Y00FE88 | AI Applications | 5 | 5 | 5 | 2.5 | 2.5 | |||||||
| 22YDS-1004 |
Master's Thesis
(Choose all ) |
30 | |||||||||||
| NY00FJ81 | Master's Thesis Design | 5 | 5 | 5 | 2.5 | 2.5 | |||||||
| NY00FJ82 | Implementation of the Master's Thesis | 20 | 6.7 | 13.3 | 6.7 | 6.7 | 6.7 | 3.3 | 3.3 | 3.3 | 3.3 | 3.3 | 3.3 |
| NY00FJ83 | Master's Thesis Reporting and Evaluation | 5 | 5 | 2.5 | 2.5 | 1.3 | 1.3 | 1.3 | 1.3 | ||||
| Total | 90 | 26.7 | 33.3 | 26.7 | 24.2 | 9.2 | 13.3 | 13.3 | 12.05 | 12.05 | 4.55 | 4.55 |
Due to the timing of optional and elective courses, credit accumulation per semester / academic year may vary.
Degree Certificate - Master's Degree (EQF 7)
Structuring for Degree Certificate for Master's Degree, according to AMK legislation. (Basic model).