FORK 2200 Preparatory Course in Programming

FORK 2200 Preparatory Course in Programming

Course code: 
FORK 2200
Department: 
Data Science and Analytics
Credits: 
0
Course coordinator: 
Wei-Ting Yang
Course name in Norwegian: 
Preparatory Course in Programming
Product category: 
Bachelor
Portfolio: 
Bachelor of Data Science for Business - Programme Courses
Semester: 
2024 Autumn
Active status: 
Active
Level of study: 
Bachelor
Teaching language: 
English
Course type: 
One semester
Introduction

This preparatory course is intended for students with no prior programming experience and introduces the most basic programming concepts in the Python programming language. The course includes lectures and practice sessions to help students to get familiar with Jupyter, an interactive programming environment to write Python code and create very simple programs.

Learning outcomes - Knowledge

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

  • understand and explain basics of how computers work,
  • understand and use the basic programming concepts in the Python programming language.
Learning outcomes - Skills

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

  • use the interactive programming environment Jupyter to write and execute Python programs,
  • implement, execute and test simple programs in Python
General Competence

Upon completion of the course the student shall have stronger competence in:

  • using computers to solve problems
Course content
  • Basics of how computers work.
  • Installation of Python and programming environments (Jupyter).
  • Basic programming concepts with a focus on Python:
    • Basic syntax
    • Variables
    • Basic data type (strings, numbers and lists)
    • Loops and conditional statements
    • Functions
Teaching and learning activities

The course consists of 8 hours of synchronous teaching and 2 hours of asynchronous learning activities (reading, additional exercises, and quizzes).

Software tools
Software defined under the section "Teaching and learning activities".
Qualifications

Higher Education Entrance Qualification

Disclaimer

Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Required prerequisite knowledge

No prerequisites required.

Type of Assessment: 
None
Total weight: 
0
Student workload
ActivityDurationComment
Webinar
8 Hour(s)
Student's own work with learning resources
2 Hour(s)
Asynchronous activities: exercises and quizzes.
Sum workload: 
10

Text for 0 credits