TECH2 Introduction to Programming, Data, and Information Technology

• 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:

  • Introduction to Python and common programming tools
  • Analyzing and visualizing data

  The first module introduces Python as well as the tools required to set up a local programming environment on the computer. 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. Students will learn the most popular programming tools in data science such as Jupyter Notebooks, Visual Studio Code, Anaconda and GitHub Copilot. Students will also learn how to use git for version control and to set up online coding repositories.

  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:

  Knowledge

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

  Skills

  • 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 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 AI tools 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 three assignments given during the semester that must be completed and approved for course approval.

  Compulsory activities from previous semesters are still valid.

• Assessment

  The assessment in TECH2 consists of two parts:

  • 3-hour digital school exam with access to Python (70%)
  • 3-day group home exam (30%). The exam will be distributed at 09:00 on day 1, with submission deadline at 12:00 on day 3.

  The home exam will be done in groups of 2-3 students. Individual work may be permitted if the student has a valid reason and receives permission from the course responsible.

  Both parts must be answered in English.

• Grading Scale

  A-F.

• Computer tools

  Python, Jupyter Notebook, git. 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 https://www.nhh.no/en/for-students/regulations/ and https://www.nhh.no/en/for-students/examinations/examination-support-materials/

• Retake

  Retake is offered early in the non-teaching semester for students who were registered for the school exam at the time of the assessment in the teaching semester, and did not achieve a passing grade. Other students may retake the exam the next time the course is offered.

  The group home exam cannot be retaken in the non-teaching semester, and may be retaken the next time the course is offered.

  For detailed information regarding the retake policy, please visit our website: https://www.nhh.no/en/for-students/examinations/retake-of-exams/https://www.nhh.no/en/for-students/examinations/retake-of-exams/ (copy url).