Academic year 2024 - 2025

•     Academic Writing OTH8HM117-3001 13.01.2025-24.03.2025  2 cr  (MAAIBUME, ...) +-
  Responsible person

  Lili Aunimo

  Teachers

  Anna Kimberley

  Campus

  Pasila Campus

  Teaching language

  English

  Timing

  13.01.2025 - 24.03.2025

  Groups

  • MAAIBUME
  • CONTACT

  Seats

  15 - 30

  Degree Programme

  AIBUM Degree Programme in AI for Business Transformation

  Evaluation scale

  H-5

  Credits

  • 2 cr

  Unit

  Master’s Degrees

•     Applied Design Research 1 RDI2HM104-3001 24.03.2025-16.05.2025  3 cr  (MAAIBUME, ...) +-
  Further information

  When the implementation type of the course is contact, online or blended it is required that the student is present during those teaching hours that are marked in the study schedule. If you are absent more than 25%, your grade will be lowered by one. If you are absent more than 50%, the course is failed.

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  Responsible person

  Lili Aunimo

  Teachers

  Lili Aunimo

  Campus

  Pasila Campus

  Teaching language

  English

  Timing

  24.03.2025 - 16.05.2025

  Groups

  • MAAIBUME
  • CONTACT

  Seats

  15 - 30

  Degree Programme

  AIBUM Degree Programme in AI for Business Transformation

  Evaluation scale

  H-5

  Credits

  • 3 cr

  Unit

  Master’s Degrees

•     Artificial Intelligence in Modern Business DIG4HM106-3021 13.01.2025-14.03.2025  5 cr  (MAAIBUME, ...) +-
  Learning objectives

  The overall learning objective of the course is to give the students insight into what artificial intelligence is and the impact it will have on the economy and business processes, as well as a hands-on knowledge and examples of how to apply artificial intelligence in different business cases.
  Upon completion of the course, the student is able to
  • Understand and describe the role of artificial intelligence in today’s business environment
  • Gain in-depth knowledge of why artificial intelligence is vital for different business processes
  • Apply artificial intelligence strategy framework
  • Understand how companies can use and leverage chatbots, cloud-based AI services and robotic process automation
  • Understand what kind of opportunities and challenges AI will create today and in the future
  • Understand and describe what skills and competences are needed in the future
  • Create a simple artificial intelligence strategy plan for any business

  Starting level and linkage with other courses

  The student will focus on the business aspects of artificial intelligence. The course does not require programming skills and the main focus is how artificial intelligence could be applied in business and how AI will change business processes. Skills and interest in a logical and systematic way of working are required.

  Contents

  - Practical examples of what artificial intelligence is and the impact it will have on the economy.
  - Benefits and challenges that AI presents to companies.
  - How artificial intelligence will transform different industries and business processes.
  - How to use the AI Strategy Framework, which will guide you on how to incorporate AI pilot programs into your overall strategy plan.
  - Examples of the five elements of the AI Strategy Framework and how to apply them.
  - Practical example of how to use the AI Strategy Framework for creating a chatbot.
  - Obtain knowledge about chatbot communication, particularly how text-only and voice-enabled chatbots work and how businesses can use them.
  - Learn how cloud-based AI services work and how companies can use them.
  - Gain a basic understanding of the business purposes for which robotic process automation can be used.
  - See examples of how AI will transform the way we work, and the skills needed for the future.
  - Develop a practical understanding of how to hire freelance AI talent.
  - Obtain knowledge of technical and non-technical AI-based jobs that will be in high demand in the future.

  Assessment criteria

  Assessment criteria - grade 1

  The student understands the basic concepts of artificial intelligence. S/he knows how AI can be used to create value for business. S/he can name different ways companies can use AI in their business processes

  Assessment criteria - grade 3

  The student has a good understanding of artificial intelligence and its application for creating value for business. S/he can create a simple artificial intelligence strategy plan

  Assessment criteria - grade 5

  The student has an excellent understanding of artificial intelligence and its application in creating value for business. S/he can create excellent artificial intelligence strategy plan and knows how to successfully apply AI

  Further information

  When the implementation type of the course is contact, online or blended it is required that the student is present during those teaching hours that are marked in the study schedule. If you are absent more than 25%, your grade will be lowered by one. If you are absent more than 50%, the course is failed.

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  Responsible person

  Kari Hiekkanen

  Learning material and recommended literature

  Artificial Intelligence: 101 Things You Must Know Today About Our Future. Lasse Rouhiainen. Amazon, 2018.
  
  The AI Advantage: How to Put the Artificial Intelligence Revolution to Work. Thomas H. Davenport. 2018
  
  Online videos, workbook and AI related business articles provided in the course.

  Teachers

  Lasse Rouhiainen

  Campus

  Pasila Campus

  Teaching language

  English

  Timing

  13.01.2025 - 14.03.2025

  Groups

  • MAAIBUME
  • CONTACT
  • BLENDED

  Seats

  15 - 30

  Degree Programme

  AIBUM Degree Programme in AI for Business Transformation

  Virtual proportion

  4 cr

  Evaluation scale

  H-5

  Credits

  • 5 cr

  Unit

  Master’s Degrees

•     Data Analytics RDI2HM102-3029 24.03.2025-16.05.2025  5 cr  (MAAIBUME, ...) +-
  Learning objectives

  Upon completion of the course, the student will:
  • Identify data sources and assess their suitability for business needs.
  • Understand the stages of data preparation, modeling, and forecasting.
  • Understand the fundamental concepts of machine learning and artificial intelligence.
  • Master methods of descriptive and explanatory analytics.
  • Be able to utilize various visualization and reporting techniques.
  • Understand the concept of information design.

  Starting level and linkage with other courses

  No prerequisites.

  Contents

  Content
  • Data analytics based on process thinking (CRISP-DM).
  • Methods for descriptive and explanatory analytics.
  • Analysis and forecasting of time series data.
  • Models for predictive analytics and machine learning.
  • Applied examples using Python.
  • Tools for visualization and reporting.

  Assessment criteria

  Assessment criteria - grade 1

  The student understands the data analytics process and can apply it, instructed by the teacher, to a business problem. The student understands the following concepts: descriptive, predictive and prescriptive analytics as well as the characteristics of advanced data and is able to solve simple business questions, guided by the teacher.
  
  The student is able to derive and visualize dashboards, scorecards and publish those using related digital tools. The students is able to apply one or some forecasting algorithms to a business problem, instructed by the teacher. The students is able to assess the reliability and relevance of business reports.

  Assessment criteria - grade 3

  The student understands the data analytics process and can apply it independently to a simple business problem. The student understands the following concepts: descriptive, predictive and prescriptive analytics as well as the characteristics of advanced data and is able to solve simple business questions independently.
  
  The students is able to derive and visualize dashboards, scorecards and publish them using related digital tools. The student is able to apply independently one or some forecasting algorithms to a business problem. The students is able to assess the reliability and relevance of business reports.

  Assessment criteria - grade 5

  The student understands the data analytics process and can apply it to a slightly complicated business problem. The student understands the following concepts: descriptive, predictive and prescriptive analytics as well as the characteristics of advanced data and is able to solve demanding business questions.
  
  The student is able to derive and visualize dashboards, scorecards and publish them using related digital tools. The student is able to apply independently several forecasting algorithms to different business problems. The student is able to assess the reliability and relevance of business reports.

  Further information

  When the implementation type of the course is contact, online or blended it is required that the student is present during those teaching hours that are marked in the study schedule. If you are absent more than 25%, your grade will be lowered by one. If you are absent more than 50%, the course is failed.

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  Responsible person

  Juha Nurmonen

  Teachers

  Juha Nurmonen

  Campus

  Pasila Campus

  Teaching language

  English

  Timing

  24.03.2025 - 16.05.2025

  Groups

  • MAAIBUME
  • CONTACT

  Seats

  31 - 50

  Degree Programme

  AIBUM Degree Programme in AI for Business Transformation

  Evaluation scale

  H-5

  Credits

  • 5 cr

  Unit

  Master’s Degrees

•     Digital Ethics DIG4HM108-3003 13.01.2025-14.03.2025  5 cr  (MAAIBUME, ...) +-
  Learning objectives

  Upon successful completion of the course, the student is able to
  - understand and analyze various ethical issues related to digitalisation and data
  - assume a critical attitude towards promises of moral improvement through digitalisation
  - see digitalisation and related technologies in their wider social, environmental and political contexts.

  Starting level and linkage with other courses

  None

  Contents

  The course will pursue a cross-disciplinary investigation of the socio-ethical implications of digital technologies. We will combine theoretical viewpoints with concrete issues facing people who are implementing and using digital systems. We will cover a variety of themes, including data ownership and control, digital economics and surveillance capitalism, power and governance of algorithmic decision making, humanization of digital technology, ethics of robotics and autonomous systems and sustainablity of digital development in general.
  
  We will take up issues that have recently come into focus and are being approached in different fields, such as health, media, games, retail, manufacturing.

  Assessment criteria

  Assessment criteria - grade 1

  The student has a basic understanding of the relationship between society and technology and what ethical risks new technologies and applications may involve.

  Assessment criteria - grade 3

  The student has a good understanding of the relationship between society and technology and what ethical risks new technologies and applications may involve. They are able to analyze and predict the ethical problems of different solutions in different industries

  Assessment criteria - grade 5

  The student has an in-depth understanding of the relationship between society and technology and what ethical risks new technologies and applications may involve. They will be able to analyse and anticipate the ethical problems of different solutions in different industries and apply different types of ethical frameworks and critical thinking widely.

  Further information

  When the implementation type of the course is contact, online or blended it is required that the student is present during those teaching hours that are marked in the study schedule. If you are absent more than 25%, your grade will be lowered by one. If you are absent more than 50%, the course is failed.

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  Learning material and recommended literature

  The course material is combination of recent academic articles, online webinars, white papers and other relevant and timely sources.

  Teachers

  Kari Hiekkanen

  Campus

  Pasila Campus

  Teaching language

  English

  Timing

  13.01.2025 - 14.03.2025

  Groups

  • MAAIBUME
  • CONTACT
  • BLENDED

  Seats

  15 - 50

  Degree Programme

  AIBUM Degree Programme in AI for Business Transformation

  Virtual proportion

  3 cr

  Evaluation scale

  H-5

  Credits

  • 5 cr

  Unit

  Master’s Degrees

•     Digital Ethics DIG4HM108-3002 24.03.2025-16.05.2025  5 cr  (EVENING, ...) +-
  Learning objectives

  Upon successful completion of the course, the student is able to
  - understand and analyze various ethical issues related to digitalisation and data
  - assume a critical attitude towards promises of moral improvement through digitalisation
  - see digitalisation and related technologies in their wider social, environmental and political contexts.

  Starting level and linkage with other courses

  None

  Contents

  The course will pursue a cross-disciplinary investigation of the socio-ethical implications of digital technologies. We will combine theoretical viewpoints with concrete issues facing people who are implementing and using digital systems. We will cover a variety of themes, including data ownership and control, digital economics and surveillance capitalism, power and governance of algorithmic decision making, humanization of digital technology, ethics of robotics and autonomous systems and sustainablity of digital development in general.
  
  We will take up issues that have recently come into focus and are being approached in different fields, such as health, media, games, retail, manufacturing.

  Assessment criteria

  Assessment criteria - grade 1

  The student has a basic understanding of the relationship between society and technology and what ethical risks new technologies and applications may involve.

  Assessment criteria - grade 3

  The student has a good understanding of the relationship between society and technology and what ethical risks new technologies and applications may involve. They are able to analyze and predict the ethical problems of different solutions in different industries

  Assessment criteria - grade 5

  The student has an in-depth understanding of the relationship between society and technology and what ethical risks new technologies and applications may involve. They will be able to analyse and anticipate the ethical problems of different solutions in different industries and apply different types of ethical frameworks and critical thinking widely.

  Further information

  When the implementation type of the course is contact, online or blended it is required that the student is present during those teaching hours that are marked in the study schedule. If you are absent more than 25%, your grade will be lowered by one. If you are absent more than 50%, the course is failed.

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  Responsible person

  Kari Hiekkanen

  Teachers

  Kari Hiekkanen

  Campus

  Pasila Campus

  Teaching language

  English

  Timing

  24.03.2025 - 16.05.2025

  Groups

  • EVENING
  • BLENDED
  • MADIGF
  • MADIGE
  • ONLINE
  • EXCH
  • MAGGU

  Seats

  31 - 60

  Degree Programme

  LUJOM Degree Programme in Business Development and Leadership, BUTEM Degree Programme in Business Technologies, LITEM Degree Programme in Business Technologies, PAKEM Degree Programme in Service Business Leadership and Development, AIBUM Degree Programme in AI for Business Transformation, LEBUM Degree Programme in Leading Business Transformation, HOSBUM Degree Programme in Tourism and Hospitality Business

  Virtual proportion

  2 cr

  Evaluation scale

  H-5

  Credits

  • 5 cr

  Unit

  Master’s Degrees

•     Management of Digital Service Development ICT4HM104-3006 13.01.2025-16.05.2025  5 cr  (MAICTE, ...) +-
  Learning objectives

  The course is an introduction to the development of digital services. The course is positioned between IT and business perspectives. Upon the successful completion of the course, the student:
  - understands the development models and principles of digital service development
  - understands technology diffusion and digital transformation
  - can identify new business roles and market changes in digital transformation
  - can identify potential value drivers, risks and measures in managing development
  - can reflect on future development opportunities and technology trends

  Starting level and linkage with other courses

  Master’s level studies. All material and communication is in English, but you may choose between English and Finnish for your report language.

  Contents

  - An introduction to digital business and digital services
  - The challenges of managing IT-based development projects
  - The development models, stakeholders, processes and measurement of digital service development
  - Digital transformation and technology diffusion models
  - New digital business models, roles and emerging technologies
  - Reflection of global IT trends and the digital future

  Assessment criteria

  Assessment criteria - grade 1

  The student partially understands development methods and principles but does not understand the role of IT in business development. Project work is limited.

  Assessment criteria - grade 3

  In addition to the skills and competences mentioned for Grade 1, the student has basic competence in planning and managing digital service development projects in a particular area. In addition, the student understands business and customer value in developing digital services. The project work demonstrates these skills and competences.

  Assessment criteria - grade 5

  In addition to the skills and competences mentioned for Grades 1 and 3, the student thoroughly understands the principles and success factors of digital service development and is able to adopt them in practice. The student can demonstrate these competences through professionally produced and completed project work. The student is able to reflect the development challenges and opportunities of digital service development in practice.

  Further information

  When the implementation type of the course is contact, online or blended it is required that the student is present during those teaching hours that are marked in the study schedule. If you are absent more than 25%, your grade will be lowered by one. If you are absent more than 50%, the course is failed.
  
  This course replaces the following course from the previous curriculum: Digitaalisten palveluiden kehittämisen johtaminen (Finnish)

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  Responsible person

  Kari Hiekkanen

  Teachers

  Ari Alamäki

  Campus

  Pasila Campus

  Teaching language

  English

  Timing

  13.01.2025 - 16.05.2025

  Groups

  • MAICTE
  • EVENING
  • BLENDED
  • ONLINE
  • MAAVBUM

  Seats

  31 - 60

  Degree Programme

  BUTEM Degree Programme in Business Technologies, AIBUM Degree Programme in AI for Business Transformation

  Virtual proportion

  3 cr

  Evaluation scale

  H-5

  Credits

  • 5 cr

  Unit

  Master’s Degrees

•     Mathematical Principles of AI DIG4HM111-3001 13.01.2025-16.05.2025  5 cr  (MAAIBUME, ...) +-
  Further information

  When the implementation type of the course is contact, online or blended it is required that the student is present during those teaching hours that are marked in the study schedule. If you are absent more than 25%, your grade will be lowered by one. If you are absent more than 50%, the course is failed.

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  Responsible person

  Lili Aunimo

  Teachers

  Toni Ernvall, Juha Nurmonen

  Campus

  Pasila Campus

  Teaching language

  English

  Timing

  13.01.2025 - 16.05.2025

  Groups

  • MAAIBUME
  • CONTACT

  Seats

  15 - 30

  Degree Programme

  AIBUM Degree Programme in AI for Business Transformation

  Evaluation scale

  H-5

  Credits

  • 5 cr

  Unit

  Master’s Degrees

•     Orientation to Ulysseys AI for Business Transformation OTH8HM116-3001 06.01.2025-16.05.2025  (MAAIBUME, ...) +-
  Responsible person

  Lili Aunimo

  Teachers

  Lili Aunimo, Mari Austin

  Campus

  Pasila Campus

  Teaching language

  English

  Timing

  06.01.2025 - 16.05.2025

  Groups

  • MAAIBUME
  • CONTACT

  Seats

  15 - 30

  Degree Programme

  AIBUM Degree Programme in AI for Business Transformation

  Evaluation scale

  H-5

  Unit

  Master’s Degrees

Academic year 2025 - 2026

There is no implementations attached to this degree programme.