VU-INN280F Business analytics III: Introduction to machine learning

Credits (ECTS):3

Course responsible:Joachim Scholderer

Campus / Online:Taught campus Ås

Teaching language:Norsk

Limits of class size:.

Course frequency:Annually

Nominal workload:75 hours

Teaching and exam period:This course starts in the Autumn parallel. This course has teaching/evaluation in the Autumn parallel.

About this course

The topic of this online course is how to use basic machine learning techniques in the company's daily business:

  • Where in your company can you use machine learning,
  • How to ensure that you have the right data,
  • How to use machine learning techniques for anomaly detection, customer segmentation and sales forecasting,
  • How to leverage the results to improve business decisions.

This course is targeted at private and public companies that want to get started with their digitalisation initiatives, employees who want to upgrade their qualifications, and people currently without employment who want to acquire future-oriented abilities and skills.

Learning outcome

Knowledge

  • Know basic machine learning techniques
  • Understand their assumptions and data requirements
  • Have an overview of how machine learning models can be used to streamline business processes

Skills

  • Be able to perform basic analyses with the help of machine learning techniques

General competence

  • Be able to work cross-functionally in business management and IT
  • Be able to contribute constructively in digitalisation and process improvement projects
  • Video lectures, exercises with data and software, independent work on two project assignments
  • Canvas and project supervision
  • Basic knowledge of statistics and data analysis
  • Portfolio assessment, consisting of two project assignments (weight: 50% each): pass/fail
  • External examiner will control the quality of the syllabus, questions for the examination, and principles for the assessment of the examination answers
    • Video lectures: 10 hours
    • Exercises with data and software: 10 hours
    • Project assignments: 40 hours
    • Self-study/syllabus literature: 15 hours
  • .
  • DAT200 (3 ECTS), INN355 (3 ECTS)
  • Passed / Not Passed
  • Minimum requirements for entrance to higher education in Norway (generell studiekompetanse)