HomeCourse

BUS337 Applications of Business Analytics

Credits (ECTS):5

Course responsible:Karl Jens Fredrik Bengtsson

Campus / Online:Taught campus Ås

Teaching language:Engelsk

Course frequency:Annually, first time autumn 2024

Nominal workload:125 hours

Teaching and exam period:This course has teaching/evaluation in autumn parallel. First time autumn 2024.

About this course

This course focuses on applications of Business Analytics. You will apply the different methods and skills that you have gained earlier in the master studies on different projects. You will work with the entire analytics process including formulating a business problem as an analytics problem, deciding what data is needed, locating, and obtaining the data, determining what data preparations are needed for the analysis, and conduct the analysis. You will practice this by working on projects from different fields of application. You will also practice creating data visualizations and presenting insights from the analysis.

Learning outcome

Knowledge

On completion of the course students should:

  • Recognize common business problems that can be solved by applying business analytics
  • Have insights in the research literature related to the problem in the chosen project

Skills

On completion of the course students should have the skills to:

  • Formulate a business problem as an analytics problem and explain its significance
  • Select the most appropriate data sources and organize data
  • Suggest and discuss analytics-based solution approaches
  • Conduct analytics-based analysis that address the problem in the project(s)
  • Present insights from the analysis, both orally and in writing, and by data visualization

General competance

  • Use creative, critical and reflective thinking to address organizational opportunities and challenges in a more digitalized and sustainable society
  • Be able to communicate with specialists and non-specialists regarding central topics within the course.
  • Develop ethical reflection and assessing social responsibility.
  • Learning activities
    Lectures, seminars, and supervision of projects
  • Teaching support
    The main lecturer is available through e-mail and phone, and for office visits by appointment, throughout the whole semester. There will also be several digital Q&A-sessions where students can attend and ask questions to the lecturer.
  • Prerequisites

    BUS336 Optimization for Business Analytics or BUS230 Operations Research, or equivalent.

    INF120 Programming and Data Processing and DAT200 Applied Machine Learning, or equivalent.

  • Assessment method

    Two assignments (groups of 1-2 people) during the semester and an oral presentation (groups of 1-2 people) towards the end of the teaching period.

    There will be no resit exam for this course. Those who do not pass the course must retake the entire course the next time it is offered.



    Portfolio Grading: Passed / Not Passed
  • Examiner scheme
    External examiner will control the quality of syllabus, exam questions, and principles for the assessment of the examination answers.
  • Mandatory activity
    None.
  • Teaching hours
    2 hours lectures per week.
  • Admission requirements
    The course is intended for students enrolled in master programmes at NMBU. It is also open for exchange students and other students with sufficient prior knowledge.