LDBA200 Applied programming

    • Number of credits
      7,5
    • Teaching semester
      2023 Autumn
    • Language of instruction
      English
    • Campus
      Lillehammer
    • Required prerequisite knowledge

      None

Course content

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

  • Concepts and principles of programming 
  • Variable types and structures and their functionality 
  • Functions, loops, assignments, subsetting and conditionals 
  • Algorithms and algorithmic thinking 
  • Programming tools for data wrangling, descriptive analyses, tests, and visualization 
  • Debugging 
  • Documentation, reproducibility, and automation 
  • Applications of programming in business, economics, and reporting 

Learning Outcome

Knowledge

Upon completion of the course, the candidate shall:  

  • Have in-depth knowledge of key concepts and principles of programming (k1) 
  • Explain and exemplify  conditional statements and loops and their use in data analysis (k2) 
  • Have advanced knowledge about documentation of packages and functions and how to use it in debugging (k3) 
  • Explain and demonstrate principles of debugging (k4) 
  • Explain and exemplify elements of algorithmic thinking in relation to data analysis (k5) 
Skills

Upon completion of the course, the candidate shall be able to: 

  • Write programs containing functions, loops, assignments, subsetting and conditionals to efficiently solve specific business problems (f1) 
  • Perform data wrangling aimed at making data amenable for analysis (f2) 
  • Debug and resolve warnings and errors independently (f3) 
  • Document data wrangling, descriptive analysis, statistical tests, and visualizations with reproducible scripts and dynamic reports (f4) 
General competence

Upon completion of the course, the candidate shall be able to: 

  • Plan and manage data analytics projects which involve use of programming and the topics covered in the course (g1) 
  • Recommend programming languages, computing tools and techniques for efficient implementation of such projects (g2) 
Teaching and working methods

The following teaching methods are used: 

  • Lectures 
  • Problem solving sessions 
  • Tutorial videos 
  • Case studies 
  • Quizzes  
Required coursework
  • Mandatory homework assignments must be handed in before each teaching module (a total of 4). These will be combinations of practical and theoretical exercises covering key topics in the course.  
  • Three out of four homework assignments must be passed to be allowed to take the exam.  
  • Attendance on at least 50% of the courses lectured teaching.
Form of assessment

48 hours individual take home exam. 

Graded A-F, where E is minimum for passing the exam.

Assessments
Form of assessmentGrading scaleGroupingDuration of assessmentSupport materialsProportionComment
Home exam
ECTS - A-F
Individual
48 Hour(s)
  • All
100%
Professional overlap
NameCreditsDateComment
KDBA200 Anvendt programmering
7,5

Reading list

Faculty
Inland School of Business and Social Sciences
Department
Department of Business Administration