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Applied Data Analytics

  • Duration: Full semester
  • Spring semester , Exchange student
  • ECTS 7,5 ECTS
  • Application period Application deadline: 15 October

Applied Data Analytics is a 7,5 ECTS course during the spring semester on the master's level. A 4-hour individual exam finalizes the course.

The single course is only open to exchange students from our partner institutions. Students applying for the English full degree must view the webpage for full degree students. 

About the course

Possible course combinations

It is not possible to choose other combinations.

 

Learning outcomes

Knowledge 

Upon completion of the course, the student can: 

  • describe the process of gathering and sampling data from various data sources, 
  • define data types and structures and explain their uses in data analysis, 
  • define conditional statements and loops and explain their use in data analysis, 
  • interpret selected descriptive statistics and data visualizations, 
  • explain elements of algorithmic thinking and 
  • discuss key findings from research on the relation between business/data analytics and business value. 

Skills 

Upon completion of the course, the student can: 

  • access and collect local and web-based data, 
  • create and manipulate data sets and shape them for further analyses, 
  • analyse the prepared data using descriptive statistics, visualizations, regression models and various business intelligence tools for data analysis and 
  • summarize key insights from data analyses into user-friendly reports. 

General competence 

Upon completion of the course, the student can: 

  • plan and manage data analytics projects which involve the topics covered in the course and 
  • recommend computing tools and techniques for efficient implementation of such projects.

 

Course content

This course provides students with a solid foundation within applied data analytics and programming. The following topics are covered. 

  • Data sources and data types 
  • Data organization and descriptive statistics 
  • Data visualization 
  • Probability and statistical interference 
  • Linear regression 
  • Business intelligence tools for data analysis

 

Teaching and working methods

The following teaching methods are used. 

  • Lectures 
  • Problem-solving sessions 
  • Tutorial videos 
  • Case studies 
  • Quizzes

 

Coursework requirements

  • Students must pass three out of four mandatory course requirements to be allowed to take the exam. 
  • 50% attendance in classes is required.

 

Examination

A four-hour individual exam under attendance.

 

Examination support material

  • Open book: The use of all software and programming tools used in the course and installed on the student’s computer is permitted.

Practical information

Requirements

Students must be enrolled in a Master's degree within the field of Business Management, Economics or similar. 

 

Housing

On-campus housing is eligible for students applying for a full semester/academic year.

General information on accommodation at Campus Lillehammer

What does it cost?

Free for exchange students

Study start information

An Orientation Week is arranged in the first week of the spring semester. The first lectures of the course are expected to begin during the same/following week. 

Would you like to apply?

The course is available only for students coming from our partner institutions. Contact the International Coordinator at your home institution to find out if you are eligible for exchange studies at Inland Norway University of Applied Sciences (INN University). Please notice that applications can be submitted for one campus only.

Application procedure and documents

Any questions?