Introduction to Programming, Data, and Information Technology

TECH2 Introduction to Programming, Data, and Information Technology

Autumn 2024

  • Topics

    TECH2 will lay the foundation for the digital workflows and computer programming skills that students will use throughout the BEDS program. Proficiency in programming, data analytics and information technology are becoming increasingly important for professionals in economics and business administration. The purpose of this course is to equip students with the knowledge needed to navigate the intersection of business and technology, and the practical skills to solve analytical problems encountered in academic and professional life.

    In TECH2, we will address the fundamental question of how to work effectively with digital tools. Students will learn basic programming in Python, which has become one of the most popular languages in both business and scientific research. These skills will be applied to implement mathematical methods from TECH1, and to access, download and analyze data on the internet to address empirical questions that arise in BUD1 and SOC1.

    The course consists of two modules:

    1. Introduction to Python and common programming tools
    2. Analyzing and visualizing data

    The first module introduces Python as well as the tools required to set up a programming environment such as Jupyter Notebooks, Visual Studio Code, Anaconda, and tools for cloud computing. Students will also learn how to use git for version control and to set up an online presence with code repositories. The second module teaches students how to access and analyze real-world data, and how Python can be used to automate routine tasks in data science.

    The course is intended for students with no or little prior programming experience. Upon successful completion of this course, students will be able to use Python as an analytical tool to solve both numerical and empirical problems.

  • Learning outcome

    Upon completion of the course, the student can:


    • Identify fundamental programming concepts such as data types, loops, functions, and modules.
    • Explain the importance of code documentation and reproducibility.
    • Employ the role of version control in coding projects.
    • Recognize the usefulness of Python in business and scientific research.


    • Set up a Python environment using Anaconda.
    • Write, modify and execute Python code.
    • Use different data types and structures in Python (e.g., list, dictionary, array).
    • Create functions and loops.
    • Load, manipulate and save data files.
    • Perform simple data analysis and visualization.
    • Use tools for cloud/remote computing.
    • Use git for version control and to create online repositories.
    • Implement control structures to handle errors and exceptions.
    • Use Python for task automation.

    General competence

    • Identify the appropriate data format for analysis (i.e., tidy data).
    • Conduct reproducible research.
    • Compare pros and cons of different Python IDEs.
    • Use package documentation and online sources for help with coding.

  • Teaching

    A combination of weekly lectures and programming workshops with practical problems that must be solved in Python.

  • Compulsory Activity

    There will be one assignment given during the semester that must be completed and approved for course approval.

  • Assessment

    The assessment in TECH2 consists of two parts:

    • 3-hour digital school exam (70%)
    • 1-week group term paper (30%)

    Note that the term paper will be group project (3-4 students) assigned in the last week of lectures. Both elements must be answered in English.

  • Grading Scale


  • Computer tools

    Python, Jupyter Notebook. Students are recommended to download the Anaconda distribution for Python. More details regarding the required software will be provided at the beginning of the course.

  • Literature

    There is no text book in this course. 

  • Permitted Support Material


    One bilingual dictionary (Category I) 

    All in accordance with Supplementary provisions to the Regulations for Full-time Study Programmes at the Norwegian School of Economics Ch.4 Permitted support material and 


ECTS Credits
Teaching language

Autumn. Offered Autumn 2024.

Course responsible

Assistant Professor Isabel Hovdahl, Department of Business and Management Science (main course responsible)

Associate Professor Richard Foltyn, Department of Economics