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Degree Programme in Data Analytics

Degree:
Bachelor of Business Administration

Degree title:
tradenomi (AMK), Bachelor of Business Administration

Credits:
210 ects

Objectives

Lot of questions, only one answer

Data analytics is a unique degree program which consists of business, data analytics and communication studies. In your studies you learn how to work in a changing business environment and get skills to start a business of your own. You learn how to manage business with data and how to create new, data driven future business.

Program is based on business studies, but core competence are data processing and presentation skills. You get knowledge to new, versatile expert- and development tasks in companies and public enterprises.

You study data analytics, communication and visualization in a context consisting of projects, company collaboration, teamwork, self-studies and expert lessons. Part of studies can be in English, so it is possible to learn practical language skills in normal studies.

It is possible to study in a real business context. You learn to know different companies and their needs in a new business area. In that way you learn to understand business and produce data needed and generate new business possibilities.

Degree programme description

Degree program consists of obligatory business and data analyzation studies and optional studies. In optional studies you can take specialized studies in an interesting field. Interships and thesis are very important parts of your studies.

If you have previous skills related to degree program thru studies, work or leisure, it is possible to apply for recognition of these.

In data analytics program you become familiar with business and business development. You learn to understand which new possibilities data analytics can give for business. According your own interest you can familiarize with other business areas as well. You learn to find, edit and present data needed by companies and to develop the company thru data. You learn to understand business and find new ideas, targets and ways to enhance data.

Degree program highlights data analytics, visualization and communication professional skills combined to business. You can add to your degree also totally different subjects eg. service design or something else you are interested in.

Implementation of studies and flexible learning tracks

Normal classroom teaching at daytime consisting lessons, webinars, company and developing projects. You learn by doing, experimenting and piloting as well as listening and understanding. Lessons are mainly Finnish, but some part of studies can be in English. Material is in Finnish or in English.

Career opportunities

After BBA graduation you have possibilities to work expert-, planning- or development kind of work in companies, municipality or government corporations. You can plan, implement, organize and develop. You can be an entrepreneur as well. You get skills needed to work in international business.

Titles can be:

Customer analyst

CDO (Chief Data Officer)

Data analyst

Data Scientist

Data visualist

Digital communication specialist

Developmet chief

Business development expert

Marketing Analyst

Project manager

Marketing analyst

Data expert

Communication spesialist

RDI and cooperation with world of work

In data analytics degree program studies are closely collaborated with companies and RDI (Research, Development, Innovation). You learn to know companies and their needs in a new business area.

In South Eastern University of Applied Sciences you develop your expertise in real company collaboration. Study environments are learning projects together with students, working life representatives and teachers. In your studies you can be working with many different projects and many different organizations.

Data analytics, part-time
Enrolment

07.11.2022 - 18.11.2022

Timing

01.01.2023 - 01.05.2023

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 60

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Juuso Koponen
  • Väinö Toots
Student groups
  • DAKV22SM
    Data analytics, part-time

Objective

You familiarize yourself with the topics from a data perspective. You can search for hot topics and related discussions and conversations about different services. You understand how data can be used to make an impact.

Content

What issues have been and are being talked about? How has the conversation been affected by data? How can I search for data about interesting discussion topics to describe the topic and the data in the discussion? What does social media automation mean?

Materials

Web materials

Teaching methods

Individual learning tracks should always be discussed with the lecturers

Employer connections

The course may have assignments made for companies or assignments agreed individually with students.

Student workload

1 cr = 27 hours work

Evaluation scale

1-5

Assessment methods and criteria

There are multiple lecturers in the course and final evaluation is based on the individual evaluations of the lecturers and the evaluation of the final project(s)

Enrolment

07.11.2022 - 18.11.2022

Timing

13.01.2023 - 31.05.2023

Credits

5 op

Virtual proportion (cr)

1 op

Mode of delivery

80 % Contact teaching, 20 % Distance learning

Teaching languages
  • Finnish
Seats

20 - 50

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Hanna Aronen
Responsible person

Hanna Aronen

Student groups
  • DAKV22SM
    Data analytics, part-time

Objective

You are able to actively use the basic professional vocabulary of your field.
You are able to look for information in English in professional sources and apply it in different study and work related communication situations.
You are able to communicate in English in various spoken and written situations in your professional field at the European level B2.

Content

What professional vocabulary is essential in your professional field?
How to look for information in professional sources in English and how to apply this information?
How to interact in spoken communication situations in English and how to draw up texts in English for professional purposes?
How to communicate in study-related situations and work communities in English?

Evaluation scale

1-5

Assessment criteria, satisfactory (1)

Ability to communicate in English orally and in writing in various situations in the professional field mainly at the European (CEFR) level B1.

Assessment criteria, good (3)

Ability to communicate in English orally and in writing in various situations in the professional field mainly at the European (CEFR) level B2.

Assessment criteria, excellent (5)

Ability to communicate in English orally and in writing in various situations in the professional field mainly at the European (CEFR) level C1.

Qualifications

If you have been instructed to participate in the Intensive course in English, you must complete it or independently acquire the equivalent knowledge and skills before you can participate in this course.

Enrolment

06.04.2022 - 22.04.2022

Timing

01.11.2022 - 31.01.2023

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 50

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Marja-Liisa Siren-Huhtinen
Responsible person

Marja-Liisa Siren-Huhtinen

Student groups
  • DAKV21SP
    Data-analytics, full-time studies

Objective

You are able to communicate in spoken and written situations in your own field.
You are familiar with the terminology of your field and able to communicate in Swedish in professional situations.

The objectives are based on the Common European Framework of Languages, level B1 and Government Decree 1129/2014.

After completing the course with the grade of 3, you are able to:
- understand clear standard and work-related speech.
- use basic structures reasonably well both in spoken and written situations.
- speak relatively fluently so that occasional mistakes in pronunciation or prosody do not lead to misunderstanding.
- describe your education and work experience for example when applying for a job.
- describe and discuss key issues of your professional field (eg. the operation, products, processes or services of companies and/or organizations).

Content

How do you use Swedish vocabulary related to education, work environment and workplace duties?
How do you use Swedish in different communicative situations of working life, for example in emails, telephoning and meetings?
How do you use the basic professional vocabulary required in your field and operational environment?

Evaluation scale

1-5

Qualifications

If you have been instructed to participate in the Intensive course in Swedish, you must complete it or independently acquire the equivalent knowledge and skills before you can participate in this course.

Enrolment

07.11.2022 - 18.11.2022

Timing

01.01.2023 - 01.05.2023

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 60

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Katariina Palmu
Responsible person

Katariina Palmu

Student groups
  • DAKV22SM
    Data analytics, part-time

Objective

You are able to describe the aspects of customer-oriented marketing concepts, including its objectives and functions. You are able to analyse customer buying behavior and define principles for the segmentation and selection of target groups. You are able to assess the effects of digital operational environment on customer-oriented marketing. You are able to design a marketing mix, taking into consideration product lifecycle, marketing objectives and corporate responsibility.

Content

What are the objectives and role of customer-oriented marketing and relationship marketing in the organizations’ operations? How does the digital economy and operational environment affect the planning of marketing? How is customer buying behavior and segmentation taken into consideration when defining objectives and target groups? What does a marketing mix consist of, and how can it be used to reach organizational goals?

Evaluation scale

1-5

Enrolment

07.11.2022 - 18.11.2022

Timing

01.01.2023 - 01.05.2023

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 80

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Väinö Toots
  • Jarkko Ansamäki
Student groups
  • DAKV22SM
    Data analytics, part-time

Objective

You can import and clean data from various sources to BI tools. You can combine data from different sources. You can calculate and change the processing of data with the BI tool. You can create different visualizations. You can publish the reports you create to your target audience. You can give a presentation based on the report you have prepared.

Content

How can BI tools be utilized in data analytics and reporting? How do I get data into tools for analysis? How is data cleaned up? How can I combine data from different sources? How can I do data calculation and other processing for data? How is data visualization done with different BI tools in terms of accessibility? How do I publish my report?

Materials

Web materials

Teaching methods

Individual learning tracks should always be discussed with the lecturers

Employer connections

The course may have assignments made for companies or assignments agreed individually with students.

Student workload

1 cr = 27 hours work

Evaluation scale

1-5

Assessment methods and criteria

There are multiple lecturers in the course and final evaluation is based on the individual evaluations of the lecturers and the evaluation of the final project(s)

Enrolment

22.08.2022 - 28.08.2022

Timing

29.08.2022 - 31.12.2022

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 55

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Atte Reijonen
Student groups
  • DAKV22SM
    Data analytics, part-time

Objective

You understand the basics of probability theory and statistics. You are able to use statistical software. You understand the principle of statistical inference.

Content

Classical and empirical definition of probability.
Connection between probability theory and statistics.
Basic concepts of statistics.
Descriptive statistics.
Statistical inference.

Evaluation scale

1-5

Enrolment

06.04.2022 - 28.08.2022

Timing

01.09.2022 - 20.12.2022

Credits

5 op

Virtual proportion (cr)

3 op

Mode of delivery

40 % Contact teaching, 60 % Distance learning

Teaching languages
  • Finnish
Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Atte Reijonen
Student groups
  • VV2022-2023
    Optional studies 2022-2023

Objective

The main objective of the course is to learn to create decision tree machine learning models using Python programming language. In the process the basics of Python programming for handling and visualizing data will be studied.

Content

The course starts from the basics of Python programming especially for handling and visualizing data. Next we will continue to decision tree machine learning models. We will go through these models theoretically and in practice using Python. Pandas, Scikit-learn and Seaborn libraries will be used among others.

Evaluation scale

Approved/Failed

Enrolment

07.11.2022 - 18.11.2022

Timing

01.01.2023 - 01.05.2023

Credits

5 op

Virtual proportion (cr)

3 op

Mode of delivery

40 % Contact teaching, 60 % Distance learning

Teaching languages
  • Finnish
Seats

20 - 60

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Pia Kaari
  • Sampo Järvinen
Responsible person

Pia Kaari

Student groups
  • DAKV21SP
    Data-analytics, full-time studies

Objective

You are able to describe human resource management as a whole and how it relates to the organization's strategy. You are able to describe the HRM processes and practices You are able to assess the quality of the organization's human resource management processes. You are able to describe the legal aspects of HRM and the most important rights and obligations of the employer and the employee.

Content

What are the processes of HRM (HRM strategy, human resource planning, recruitment, induction, training, development, compensation, measurement and reporting)? How has the HRM developed and what issues are currently relevant? What are the key labor laws that the employee, employer and HRM personnel must take into account?

Evaluation scale

1-5

Qualifications

Business and entrepreneurship, Financial accounting, or equivalent knowledge

Enrolment

22.08.2022 - 28.08.2022

Timing

29.08.2022 - 09.12.2022

Credits

5 op

Virtual proportion (cr)

5 op

Mode of delivery

Distance learning

Teaching languages
  • Finnish
Seats

20 - 300

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Juuso Koponen
  • Väinö Toots
  • Jarkko Ansamäki
Responsible person

Jarkko Ansamäki

Student groups
  • DAKV22SM
    Data analytics, part-time

Objective

You understand the importance of data analytics for businesses. You know the basic concepts of data analytics. You know different data sources. You understand the importance of visualization and communication. You know some programs related to data analytics. You can do small analyzes on a simple data set using a spreadsheet program. You understand your responsibilities and are able to take sustainability into account when preparing reports. You examine data critically.

Content

What is the significance of data analytics? Where can I get data? How has the presentation of the data been able to make an impact? What programs can be utilized in data analytics? How can I do a simple analysis on open data using a spreadsheet program? What mathematical bases do I need when analyzing data? How do I act responsibly and with sustainability in mind? How do I make accessible reports?

Materials

The course uses online materials, which are announced on the course platform as the course progresses.

Teaching methods

This is an online course that will be done as it is. However, students can proceed at their own pace within the limits set by the start and end dates of the course.

Employer connections

-

Exam schedules

The exams that you want to be included in the calculation of the overall grade must be completed by the end date of the implementation.

International connections

-

Student workload

1 cr = 27h student work

Content scheduling

-

Further information

There is no possibility of renewal in the course, but you must register for a new implementation in order to renew or get better grade.

Evaluation scale

1-5

Assessment methods and criteria

Assessment is based on online exams with questions about the theory and the tasks.

There is no possibility of renewal in the course, but you must register for a new implementation in order to renew or get better grade.

Enrolment

06.04.2022 - 22.04.2022

Timing

29.08.2022 - 31.12.2022

Credits

5 op

Virtual proportion (cr)

2 op

Mode of delivery

60 % Contact teaching, 40 % Distance learning

Teaching languages
  • Finnish
Seats

20 - 40

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Mervi Koskelainen
Student groups
  • DAKV21SP
    Data-analytics, full-time studies

Objective

You are able to analyze the international business environment. You can identify global business opportunities and prerequisites and analyze market areas. You are familiar with the strategies of international operations. You are able to compare different operation models and select the most appropriate model for the company.

Content

What are the most important features in the international business environment? What are companies' opportunities and prerequisites related to international operations? What are the strategies of international operations? How to select the most appropriate operation model? What are Russian ways and corporate culture in your field of business?

Evaluation scale

1-5

Enrolment

07.11.2022 - 18.11.2022

Timing

11.01.2023 - 01.05.2023

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 40

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Atte Reijonen
  • Jarkko Ansamäki
Student groups
  • DAKV21SP
    Data-analytics, full-time studies

Objective

You understand the principles of artificial intelligence and machine learning.
You can determine what type of machine learning is appropriate for a given task.
You can do small artificial intelligence projects.

Content

How does artificial intelligence work?
How can machine learning be classified?
What are the different machine learning solutions suitable for?
How can simple artificial intelligence solutions be made?

Materials

Web materials

Teaching methods

Individual learning tracks should always be discussed with the lecturers

Employer connections

The course may have assignments made for companies or assignments agreed individually with students.

Student workload

1 cr = 27 hours work

Evaluation scale

1-5

Assessment methods and criteria

There are multiple lecturers in the course and final evaluation is based on the individual evaluations of the lecturers and the evaluation of the final project(s)

Enrolment

07.11.2022 - 18.11.2022

Timing

11.01.2023 - 15.05.2023

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 60

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Satu Peltola
Student groups
  • DAKV21SP
    Data-analytics, full-time studies

Objective

You know how to collect and analyze qualitative data.
You can use software and artificial intelligence to analyze qualitative data.

Content

How can qualitative data be collected in different ways?
How is qualitative data analyzed?
How can different programs be utilized in the collection and analysis of qualitative data?
How can artificial intelligence be utilized in the analysis of qualitative data?

Evaluation scale

1-5

Enrolment

06.04.2022 - 22.04.2022

Timing

29.08.2022 - 31.12.2022

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 40

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Katariina Palmu
Student groups
  • DAKV21SP
    Data-analytics, full-time studies

Objective

You understand what different business metrics tell. You can calculate different indicators. You know where to find the data used to calculate the various indicators.

Content

What elements are measured in different companies? What do the different key figures tell about the company's operations? How are the different indicators calculated? Where do the figures needed for the calculation come from? How are indicators used in companies?

Materials

Web materials

Teaching methods

Individual learning tracks can be discussed about with the lecturer

Employer connections

The course may have assignments made for companies or assignments agreed individually with students.

Student workload

1 cr = 27 hours work

Evaluation scale

1-5

Assessment methods and criteria

Evaluation according given exercises and projects.

Enrolment

22.08.2022 - 28.08.2022

Timing

25.08.2022 - 31.12.2025

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 55

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Väinö Toots
  • Jarkko Ansamäki
Responsible person

Jarkko Ansamäki

Student groups
  • DAKV22SM
    Data analytics, part-time

Objective

You act responsibly as a student and a member of the university community.
You are able to set learning objectives, plan your study and career path, follow your progress in studies and assess your learning.
You are able to improve your working life competencies.
You know how to act according to the ethical principles of your field.
You are able to promote your skills and competencies.

Content

What is Xamk like as a study community and learning environment?
How do you create a personal study and career plan?
How do you identify your skills and competences?
How do you improve your general competences?
What are your profession and line of work like?
What ethical principles are relevant to your field?
How do you promote your competences and strengthen your skills with respect to applying for jobs?
How do you enhance continuous learning?

Materials

Will be announced during the course

Teaching methods

Discussion with the lecturer needed

Student workload

1 cr = 27 hours work for the student

Evaluation scale

Approved/Failed

Enrolment

14.03.2023 - 31.03.2023

Timing

02.05.2023 - 31.07.2023

Credits

20 op

RD proportion (cr)

20 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

1 - 100

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Jarkko Ansamäki
Student groups
  • DAKV21SP
    Data-analytics, full-time studies

Objective

You practice the key tasks of your field under guidance.
You apply theoretical knowledge in practice.
You develop your capability of independent and effective working.
You are able to complete tasks in your field of specialization.

Content

You find a training place suitable for your specialization.
You carry out assignments related to the field of business data analytics and visualisation during the training period.
You report on the training according to instructions.

Materials

-

Teaching methods

Each training is individual

Employer connections

The internship is practical training

Exam schedules

-

International connections

The internship can also be completed abroad

Student workload

Training workloads:
Basic internship 10 credits, approx. 7 working weeks / 263 h
Advanced training 20 credits, approx. 13 working weeks / 488 h.

Evaluation scale

Approved/Failed

Enrolment

06.04.2022 - 22.04.2022

Timing

29.08.2022 - 31.12.2022

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 40

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Väinö Toots
Student groups
  • DAKV21SP
    Data-analytics, full-time studies

Objective

You can describe a relational database.
You can collect data from business databases for analyzing with SQL-language.
You know the basics of the data warehouse.

Content

How to use databases?
How to collect data from business databases with SQL-language?
How to take advantage of data warehouse in business intelligence?

Materials

Web materials

Teaching methods

Individual learning tracks can be discussed about with the lecturer

Employer connections

The course may have assignments made for companies or assignments agreed individually with students.

Student workload

1 cr = 27 hours work

Evaluation scale

1-5

Assessment methods and criteria

Evaluation according given exercises and projects.

Enrolment

07.11.2022 - 18.11.2022

Timing

01.01.2023 - 01.05.2023

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 60

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Atte Reijonen
Student groups
  • DAKV21SP
    Data-analytics, full-time studies

Objective

You can analyze data sets using statistical methods. In particular, you will be able to perform statistical tests and modify data using mathematical software.

Content

How can different phenomena be described using statistical methods? How are statistical data analyzed? How can you leverage different software for statistical analysis?

Evaluation scale

1-5

Enrolment

07.11.2022 - 18.11.2022

Timing

01.01.2023 - 01.05.2023

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 60

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Katariina Palmu
  • Emmi Mäkinen
  • Satu Peltola
Student groups
  • DAKV22SM
    Data analytics, part-time

Objective

Common learning outcomes (as implemented in degree programmes) 2 ECTS credits:

You know the general stages in a research and development process.
You are able to search for information in the key information environments of your own field.
You are able to read, critically evaluate and utilize the literature and research publications of your own field.
You are familiar with and able to apply the principles of research ethics and reliability.
You are able to compose a literature review based on the materials published in your field of study and your own bachelor’s thesis following the principles of scientific communication.

Degree programme specific learning outcomes for research and development methods, 3 ECTS credits

You are familiar with the current research subjects and development needs of your own field.
You are familiar with and able to apply the key development approaches and/or research methods and ethical principles of your own field.
You are able to report on a research or development process following the principles of professional and scientific communication.

Content

Content of common learning outcomes, 2 ECTS credits:

What are the phases into which a research and development process can be divided?
How do you find, read and critically evaluate the research data of your own field?
How do you write a literature review that utilizes reliable research data and is linked to your own field and bachelor’s thesis following the principles of ethical scientific communication?

Degree programme specific content, 3 ECTS credits

What are the key research subjects and development needs in your own field?
What are the development approaches and/or research methods in your own field and how do you apply them in practice based on the development needs of your own field?
How do you report a research or development process following the principles of ethical professional and scientific communication in your own field?

Evaluation scale

1-5

Enrolment

22.08.2022 - 28.08.2022

Timing

29.08.2022 - 31.12.2022

Credits

5 op

Virtual proportion (cr)

2 op

Mode of delivery

60 % Contact teaching, 40 % Distance learning

Teaching languages
  • Finnish
Seats

20 - 70

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Tuomo Kettula
Responsible person

Tuomo Kettula

Student groups
  • DAKV22SM
    Data analytics, part-time

Objective

You are able to use suitable ICT applications individually and in teams. You are able to compose documents, presentation graphics and spreadsheets. You are able to work in compliance with information security regulations.

Content

What ICT applications are commonly used during studies and at work? How to produce documents, presentations and spreadsheets with IT applications? What is information security and how to comply with it during studies and at work?

Evaluation scale

1-5

Enrolment

07.11.2022 - 18.11.2022

Timing

09.01.2023 - 01.05.2023

Credits

5 op

Virtual proportion (cr)

5 op

Mode of delivery

Distance learning

Teaching languages
  • Finnish
Seats

20 - 200

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Jarkko Ansamäki
Responsible person

Jarkko Ansamäki

Student groups
  • DAKV22SM
    Data analytics, part-time

Objective

You understand what elements can be measured in various online services and what they might tell. You can use the analysis tools of different services to analyze traffic. You can import data from systems elsewhere for analysis. You can combine data from different sources and perform analyzes based on the combined data.

Content

What information is available about the users of various web services and social media? How can data be collected? In what ways can data be analyzed? What meanings are hidden behind the data stream?

Materials

The course uses online materials, which are announced on the course platform as the course progresses.

Teaching methods

This is an online course that will be done as it is. However, students can proceed at their own pace within the limits set by the start and end dates of the course.

Employer connections

-

Exam schedules

The exams that you want to be included in the calculation of the overall grade must be completed by the end date of the implementation.

International connections

-

Student workload

1 cr = 27h student work

Content scheduling

-

Further information

There is no possibility of renewal in the course, but you must register for a new implementation in order to renew or get better grade.

Evaluation scale

1-5

Assessment methods and criteria

Assessment is based on online exams with questions about the theory and the tasks.

There is no possibility of renewal in the course, but you must register for a new implementation in order to renew or get better grade.

Enrolment

22.08.2022 - 28.08.2022

Timing

29.08.2022 - 31.12.2022

Credits

5 op

Virtual proportion (cr)

2 op

Mode of delivery

60 % Contact teaching, 40 % Distance learning

Teaching languages
  • Finnish
Seats

20 - 50

Degree programmes
  • Degree Programme in Data Analytics
  • Degree Programme in Digital International Business
Teachers
  • Miia Karttunen
Responsible person

Miia Karttunen

Student groups
  • DAKV22SM
    Data analytics, part-time
  • IBKV22SP
    Digital international business, full-time studies

Objective

You understand the significance of interaction as part of your professional expertise and you can act appropriately in various communication situations.
You are familiar with Xamk's instructions for written assignments.
You are able to search reliable information and use it ethically.
You can express your views justifying them based on facts and use standard Finnish appropriate in each context.
You know how to write texts that meet the standards for layout, content and style required in your studies and in your own field, and use appropriate tools and forums.
You improve your interactive communication skills and manage fluently in different cooperation situations, such as meetings and negotiations.
You develop your presentation skills for professional purposes and acquire skills in giving and receiving feedback.

Content

What interaction skills are required in your own studies and in workplaces in your field?
How do you justify your views using standard Finnish?
How do you search reliable information from different sources and use it ethically?
Which written skills (genres, styles, tools) should you master both in your studies and in work assignments in your own professional field?
How do you utilize language regulations and tools in your studies and workplace communication?
Which skills do you need in presentations, meetings and negotiations?
How do you assess your own communication skills and ease your stage fright?
How do you give constructive feedback?
How do you utilize the feedback you received?

Materials

The online learning environment Learn and included material.

Teaching methods

This course is for the students in the degree prorgammes of data-analytics and native-Finnish students in Digital International Business. The course suits also for other students in the field of business.

Employer connections

Field-spesific assignments for the working life purposes, integrated assignments in co-operation with degree programmes.

Exam schedules

There are two online exams, see the course schedule.

Student workload

135 hours of work (incl. lectures, assignments, independent work, teamwork)

Content scheduling

- written communication in my professional field
- oral communication in my professional field
- information retrieval and referencing
- team communication, meetings

Further information

When you have done the enrollment, wait until the registration time is over. After that the course teacher accepts your registration. The information for the starting (schedule, online environment, assignments) this course will be published at the first meeting. For further information, please contact the teacher.

Evaluation scale

1-5

Assessment methods and criteria

The assessment bases on the assignments and active participation. More detailed description of the assessment available at the online environment Learn.

Enrolment

06.04.2022 - 22.04.2022

Timing

29.08.2022 - 31.12.2022

Credits

5 op

Mode of delivery

Contact teaching

Teaching languages
  • Finnish
Seats

20 - 40

Degree programmes
  • Degree Programme in Data Analytics
Teachers
  • Väinö Toots
  • Jarkko Ansamäki
Student groups
  • DAKV21SP
    Data-analytics, full-time studies

Objective

You have an understanding of the different systems used by companies and the data they contain. You are familiar with the proprietary reporting features of some popular software. You can import data from different systems elsewhere for reporting and analysis.

Content

What kind of data do different companies use internally? Where is this data collected? Where is it stored? How is it utilized? How can it be analyzed?

Materials

Web materials

Teaching methods

Individual learning tracks should always be discussed with the lecturers

Employer connections

The course may have assignments made for companies or assignments agreed individually with students.

Student workload

1 cr = 27 hours work

Evaluation scale

1-5

Assessment methods and criteria

There are multiple lecturers in the course and final evaluation is based on the individual evaluations of the lecturers and the evaluation of the final project(s)