LDBA200 Applied programming
- Number of credits7,5
- Teaching semester2023 Autumn
- Language of instructionEnglish
- CampusLillehammer
- Required prerequisite knowledge
None
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
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)
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)
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)
The following teaching methods are used:
- Lectures
- Problem solving sessions
- Tutorial videos
- Case studies
- Quizzes
- 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.
48 hours individual take home exam.
Graded A-F, where E is minimum for passing the exam.
| Form of assessment | Grading scale | Grouping | Duration of assessment | Support materials | Proportion | Comment |
|---|---|---|---|---|---|---|
Home exam | ECTS - A-F | Individual | 48 Hour(s) |
| 100% |
Reading list
No reading list available for this course