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Content of the programme

Data Skills

Course name: Data Skills

Period: International Business Consultancy (Y4:13/14)

Cluster within the International Business Consultancy Programme: Business Skills and Languages

Study load: 2 ECTS (~56 hours)

Course description

Data is booming and being able to work with, analyze and interpret data is becoming an increasingly important skill. During this course you will work on this skill via a hands on approach. After this course you are able to apply the basics of dataanalysis and advice organizations with data questions.

Competences and learning objectives

Competences: information management, designing and changing

Learning objectives

  • Explain what the difference between data and information is;
  • Interpret and work with different types of data;
  • Understand and explain the difference; between correlation and causation;
  • Decide which analytical tool is best for answering a question;
  • Explain the basic structures of date;
  • Create and interpret data visualizations;
  • Execute and interpret a basic linear; regression analysis;
  • Execute and interpret a basic classification analysis;
  • Work with Python.

General course information

Required previous knowledge

Basic knowledge of Microsoft Excel is required. Basic knowledge of statistics is considered useful, but not mandatory.

https://www.khanacademy.org/math/statisticsprobability Rosling, H., (2018). Factfulness: Ten Reasons We're Wrong About The World - And Why Things Are Better Than You Think (1st edn.). Hodder & Stoughton: London, UK. Weekly prescribed articles, readings, videos, tutorials and/or datasets.

Way of working

During classes you will analyze data hands on. It is expected that you come to class prepared (i.e. read the prescribed texts/watch the prescribed videos). Additionally a weekly discussion on trends, innovation and the impact of data (analysis) will be held.

Exam

Weekly data analysis assignments (together 60% of your final grade). Create a poster/infographic using quantitative data analysis to help answer a business/economic/social science research question of your choosing (40% of your final grade).

Caesura

A final score of 5,5 or higher leads to passing the course and receiving the related 2 ECTS.

Retake exam

The retake of the exam is scheduled at the end of the semester. This is usually two or three weeks after the first exam week.