Software industry’s course sets for Digital transformation

Application period and applying to UEF's courses

Application period is continuous and courses can be completed until the end of 2022. Applying is possible by filling application form.

Selection criteria

1. Applicant training needs in project's courses or course sets and their suitability to project's goals
2. Applicant ability to pass courses with their study background and other skills.
3. Applicants learning skills and possibilities to participate the courses.
4. Applicant suitability to project's target groups (over 55 years old, more than 10 years from graduation, immigrant or employee in cooperative company)

Applicants who fill all 4 criteria well are selected. Also applicant who fill criteria 1-3 very well can be admitted.

Basic university courses at University of Eastern Finland may contains lectures (at the university or online), exercises (at the university or online) and exam (at the university or online). The parts that can be done online vary between courses.

Online course is a course, where course materials and teaching is online. Online course pages include lecture recordings and lecture streams and exercises. The online course webpage includes information about the course literature.

MOOC-course is an online course which is located in digicampus.fi and can be conducted during Academic year 2021-22. All exercises must be completed before deadline to get a course grade.

Most of the courses are in Finnish but some of the courses can be done in English. Courses that can be done in English are with bold font.

University of Eastern Finland courses

Open in Academic year 2021-2022:

• Programming 1 / Introduction to Python 5 Cp

Autumn 2021:

• Computer Systems 5 cp
• Short Introduction to Algorithmic Data Analysis 3 Cp
• Introduction to Statistics 3-5 Cp
• Probabilistic inference for data science 1, 5 Cp
• Statistical Data analysis 6 Cp *
• Introduction to Computing 5 Cp **
• Computer Systems 5 Cp
• Insights from data 4 Cp ***

Spring 2022:

• Basics in Statistics 3-5 Cp
• Introduction to Artificial Intelligence 4 Cp
• Probabilistic inference for data science 2, 5 Cp

* Last year's lectures are recorded in English. Exercises and material are in English.

** Book examination in English, otherwise course will be held in Finnish

*** Some course material is in English

The course sets of the project in University of Eastern Finland and in cooperative Universities:

University of Eastern Finland:

• Basics of Computing
  • Introduction to Computing 5 Cp
  • Programming I / Introduction to Python Programming 5 Cp (MOOC), linked to WebOodi
  • Computer systems 5 Cp
  • Design on Information Systems 5 Cp
• Digitalisation
  • Digital School 2 Cp (MOOC)
  • Digitalization and Conversational 2 Cp (MOOC)
  • Introduction to Artificial Intelligence 4 Cp
  • Human Factors of Interactive Technology 5 Cp (online course)
• Basics of Data-analysis
  • Insights from data 4 Cp
  • Business-oriented data analytics 4 Cp 
  • Short Introduction to Algorithmic Data Analysis 3 Cp
  • Introduction to Statistics 3-5 Cp
  • Basics in Statistics 3-5 Cp
• Advanced data-analysis
  • Probabilistic inference for data science 1, 5 Cp
  • Probabilistic inference for data science 2, 5 Cp
  • Statistical Data analysis 6 Cp

University of Helsinki:

• Cloud-based web applications (Pilvipohjaiset websovellukset) Fullstack and DevOps with Docker -courses are in English
• Programming, (Ohjelmointi) Haskell is only in English 
• Cyber Security Base
• AI and Data (Tekoäly ja data)

We are recommending to start with  "Aloita tästä" (start here) courses if subject is unfamiliar. Some courses can be done in English and in other languages, but not all. Bold texts can be completely completed with English. Note: course sets does not show in English mooc-page.

LUT:

• Software Engineering Studies

The course is held either in English or in Finnish.

If you are interested in cooperations with the project, please contact to laura.toivanen@uef.fi with a title cooperation or co-operation with following information:

• Cooperation name (i.e. project or company)
• Interested courses or course sets
• Introduction
• Logo and link (optional)