Please select the curriculum by the start year of studies and track.
English
Individual learning tasks
Small group work online
Webinars
Online Discussions
Recorded online lectures, podcasts
Dodd, S-J. & Epstein, I. 2012. Practice-based research in social work: a guide for reluctant researchers. London; New York: Routledge.
OR
Bryman, A. 2012. Social research methods. Oxford: Oxford University Press cop.
OR
Burns, N. & Grove, S. K. 2001. The practice of nursing research. Conduct, Critique, and Utilization. 5th edition or the latest. Philadelphia : Elsevier/Saunders cop.
OR
Polit, D. F. & Beck, C.T. 2014. Essentials of nursing research: appraising evidence for nursing practice. Philadelphia : Wolters Kluwer Health/Lippincott Williams & Wilkins cop.
OR
Yin, R. K. 2018. Case study research and applications : design and methods. Los Angeles: Sage.
Ben Waller, Kaisa Lällä
29.08.2022 - 21.12.2022
webinars 16 h
- learning tasks 80 h
- studying the course material 40 h
Total 135 hours.
01.08.2022 - 04.09.2022
0 - 20
Master's Degree Programme in Sport and Exercise Physiotherapy, Master's Degree Programme in Artificial Intelligence and Data Analytics, Master's Degree Programme in Information Technology, Full Stack Software Development, Master's Degree Programme in Professional Project Management, Master's Degree Programme in International Business Management, Master's Degree Programme in Information Technology, Cyber Security
Face-to-face
School of Health and Social Studies
English
WEBINAR & WORKSHOP days are planned to happen on ZOOM platform
The teacher zoom classroom link will be given close to the start of the course via Peppi's e-mail
This course is ONLINE on ZOOM
Please note seminar & workshop days are:
Friday 07.10.2022 from 14.30 pm to 19.30
Saturday 08.10.2022 from 10.00 am to 15.00
and
Friday 11.11.2022 from 14.30 pm to 19.30
Saturday 12.11.2022 from 10.00 am to 15.00
The course is meant as an intensive seminar/workshop journey where the student experience:
1. Experiential learning
2. Individual & Collective Coaching
3. Network activation
4. Executive process and follow up
5. Awareness-based leadership & decision making
As guiding books:
- Daft, R. 2015-2018. The Leadership Experience, 6h or 7th Edition – CENGAGE Learning 2015-2018
- Northouse, P. 2016. Leadership: Theory and Practice. Sage Publications.
A topical non-fiction book on human leadership.
Other:
Teacher's publications & material
Marcella Zoccoli
01.09.2022 - 31.12.2022
The passing of the course requires active participation on seminar & workshop days
- Individual work 30%
- Project-base collective work or workshop training 70%
01.08.2022 - 02.09.2022
Leadership Dynamics
Overview & ''Polaroid'' on Leadership theories & styles
Leadership Total Awareness
Emotional intelligence & other human intelligences
Communication & Intra- and Interdependent relational skills
Leading in the present Change towards a transformative Future
0 - 30
Master's Degree Programme in Artificial Intelligence and Data Analytics, Master's Degree Programme in Information Technology, Full Stack Software Development, Master's Degree Programme in Professional Project Management, Master's Degree Programme in International Business Management, Master's Degree Programme in Information Technology, Cyber Security
Face-to-face
School of Technology
English
Lectures
Literature
Video material
Exercises and assignments
Guidance and feedback
Aki Laaksonen
The course does not include an exam.
01.09.2022 - 31.12.2022
Allocation of time on various tasks and student work load in total 135h
Lectures 14h
Independent familiarization with literature and videos 40h
Independent exercises and assignments 81h
01.08.2022 - 25.08.2022
Accreditation (replacement and inclusion)
Recognition of informal learning
Studification
Further instructions can be found in the Degree Regulations and in the Master's Degree study guide.
The assessment of the course is based on the following credits:
1) exercises and assignments (100%, 5 ECTS)
Master's Degree Programme in Artificial Intelligence and Data Analytics, Master's Degree Programme in Information Technology, Full Stack Software Development, Master's Degree Programme in Professional Project Management, Master's Degree Programme in International Business Management, Master's Degree Programme in Information Technology, Cyber Security
Online learning
5 cr
School of Business
English
Online implementation.
Sessions in Tuula's Zoom.
THIS IS AN ONLINE IMPLEMENTATION with webinars approx. one per month.
Individual learning tasks: e.g. Elevator speech, essays, small reports, videos
Small group work online
Webinars
Online Discussions
Recorded lectures or lectures in webinars
Bryman, A. 2012. Social research methods. Oxford: Oxford University Press cop.
Ethical principles and ethical review in human sciences. 2020. Finnish National Board on Research Integrity. www.tenk.fi/en
Kananen, J. 2011. Rafting through the Thesis Process. Jyväskylä: Jyväskylä University of Applied Sciences.
Responsible conduct of research and procedures for handling allegations of misconduct in Finland. 2012. Finnish National Board on Research Integrity. www.tenk.fi/en
Tang, H. 2021. Engineering Research. Design, Methods, and Publication. John Wiley and Sons Inc..
Tuula Kotikoski
If possible, also webinars with R&D experts from the working life
Lutakko Campus
09.01.2023 - 28.04.2023
- six online webinars 12 h
- webinars with guest speakers if guest speakers available 0-4 h
- learning tasks 50 h
- studying the course material 72 h
Total 135 hours of student work.
01.11.2022 - 05.01.2023
Online Implementation:
Presenting on the online discussion platform is a sign of your participation in the course and it can be confirmed by completing the Ethics task.
The course is modular, which means it takes 2-3 weeks to complete the materials and learning tasks of each of the five modules.
The course has 2-3 webinars in modules 1 and 2 if guest speakers can be arranged.
You can complete the course by combining study and work, by studification. Agree on studification of the course with the lecturer in charge of the course. For more information on studification, see the degree regulations and study guide.
0 - 35
Avoin AMK 5 (not translated)
Master's Degree Programme in Artificial Intelligence and Data Analytics
Face-to-face
School of Technology
English
Contact instruction over 2 weekends: on Fridays at 2pm - 8pm, and on Saturdays at 9am - 3pm.
Location: IT-Dynamo, Piippukatu 2, 40100 Jyväskylä.
Contact instruction over 2 weekends during the semester.
Exercises and distance learning between the contact sessions.
Study project covering a topic based on individual needs.
Further defined during the first contact session and more can be found in the slide sets.
Relevant parts of the following books:
The Essential AI Handbook for Leaders
by Peltarion (59 pages).
Ethical Artificial Intelligence
by Bill Hibbard (2015, 177 pages).
The Quest for Artificial Intelligence: A History of Ideas and Achievements
by Nils J. Nilsson (2009, 707 pages).
A Brief Introduction to Machine Learning for Engineers
by O. Simeone (237 pages)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd edition (corrected)
by Trevor Hastie, Robert Tibshirani, and Jerome Friedman (2017, 764 pages).
Python Data Science Handbook: Essential Tools for Working with Data
by Jake VanderPlas (2016 O'Reilly Media, 541 pages).
pandas: powerful Python data analysis toolkit
by Wes McKinney and the Pandas Development Team (2020, 3071 pages).
Tuomo Sipola
It is advisable that the students use their own work environment as an object of study and as a data source.
Possible guest lecturers from companies.
Lutakko Campus
26.08.2022 - 16.12.2022
5 ECTS credits equals about 135 hours of study work.
Contact instruction: 24 hours
Exercises: 48 hours
Study project: 63 hours
01.08.2022 - 04.09.2022
0 - 35
Feedback on exercises and study project.
Self evaluation of study project.
Peer evaluation of study project.
Teacher's evaluation of study project.
Open UAS 5
Master's Degree Programme in Artificial Intelligence and Data Analytics
Face-to-face, Online learning
4 cr
School of Technology
English
Online lectures (recorded) and exercise sessions.
Two campus meetings (Fri-Sat): Jan 13-14 and Mar 10-11, 2023
Online material.
Harri Varpanen
Lutakko Campus
No exams.
09.01.2023 - 28.04.2023
01.11.2022 - 05.01.2023
Seven sets of theory / exercises:
1. Orientation (basics, numpy, matrices)
2. Data manipulation (pandas)
3. Data visualization (matplotlib & seaborn)
4. Time series (pmdarima)
5. Linear regression (scipy / sklearn)
6. Logistic regression (scipy / sklearn)
7. Dimension reduction (scipy / sklearn).
Uni. Helsinki: Data Analysis with Python (MOOC), course code CSM90004
0 - 35
The grade is determined by the number of completed exercises.
Basic knowledge of python is assumed.
Master's Degree Programme in Artificial Intelligence and Data Analytics
Face-to-face, Online learning
4 cr
School of Technology
English
Mandatory contact days:
Sat 10.9.2022 klo 9-15
Fri 18.11.2022 klo 15-20
Mika Rantonen
Lutakko Campus
29.08.2022 - 16.12.2022
01.08.2022 - 04.09.2022
0 - 35
Master's Degree Programme in Artificial Intelligence and Data Analytics
Face-to-face
School of Technology
English
Virtual study, contact study.
Lecture notes, exercises, video examples
Muller, Guido: Introduction to Machine Learning with Python
Tomi Nieminen
Lutakko Campus
29.08.2022 - 16.12.2022
Virtual study 110 h
Contact study 15 h
01.08.2022 - 04.09.2022
0 - 35
Master's Degree Programme in Artificial Intelligence and Data Analytics
Face-to-face
School of Technology
There is no implementations attached to this degree programme.
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.
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.
Students can take the studies part-time (in 3 years) based on their preference. Most of the courses are implemented by blending in-class activities with learning in virtual environments. Students can choose their electives from master level courses of other degree programmes or from CampusOnline, Edufutura, Yritystehdas, and Future Factory. Prior learning can be recognized via other master level studies or through work experience based on discussions with course instructors.
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 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.
There are no specific degree-related or statutory qualification requirements in the field.
The graduate may apply to continue on to postgraduate studies in science or arts at universities (Act 558/2009, Section 37) and in the school of professional teacher education. The studies can be continued by applying e.g. to corresponding post-degree education at universities abroad. 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.
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.