Course - Health data analysis and Python - IT6118
Health data analysis and Python
Assessments and mandatory activities may be changed until September 20th.
About
About the course
Course content
The course introduces using the Python programming language to perform data analysis on real-world health data. Teaching combines theoretical lectures and practical hands-on exercises.
Learning outcome
Knowledge
The studenten should be able to:
- Learn basic Python, one of the most popular programming languages for data analysis
- Perform exploratory data analysis and visualize summary statistics using the Python libraries
- Perform simple operations on databases to extract information using Structured Query Language (SQL).
Skills
The student should be able to:
- Perform simple operations on real-world health data
- Summarize and communicate result
Learning methods and activities
Lectures and in-class laboratory exercises.
Compulsory assignments
- Participation in seminars
Further on evaluation
The exam in this course is a portfolio with three assignments, which all count equally of the grade. All assignments must be submitted individually throughout the semester in the following order:
1) Assignment 1 – Introduction to programming in Python (submission around week 4)
2) Assignment 2 – Exploration and processing of health data with Pandas (submission around week 15)
3) Assignment 3 – From analysis to report (submission around week 19)
The complete portfolio is then submitted as a whole at the end (around week 21). Scoring by points on the individual assignments and by letter grade on the overall portfolio. Guidance is provided during the class sessions and, if needed, between them.
In case of re-sit exam, the entire portfolio must be submitted again.
Students who have fulfilled the required attendance at the class sessions (compulsory activity) do not need to complete this again in case of repetition of the exam.
Specific conditions
Admission to a programme of study is required:
Healthcare Informatics (MHI)
Recommended previous knowledge
New to programming or need to brush up on your programming skills? Learn to code with these beginner-friendly courses:
· Get started with Python, if you have no coding experience: https://www.kaggle.com/learn/intro-to-programming/
· Learn the most important language for data science: https://www.kaggle.com/learn/python/
Required previous knowledge
Three years of higher education (college / university) and at least two years of relevant work experience after completed degree (admission requirements for the master's program in healthcare informatics).
Course materials
· Downey, A. (2024). Think Python: How to think like a computer scientist (Third edition). O’Reilly Media, Inc. https://allendowney.github.io/ThinkPython/
· McKinney, W. (2022). Python for data analysis: Data wrangling with pandas, NumPy, and Jupyter (Third edition). O’Reilly. https://wesmckinney.com/book/
Special requirements for equipment and computer tools. Access to your own computer is required. More information to come.
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| IT6102 | 1.2 sp | Autumn 2025 |
| IT6104 | 1.2 sp | Autumn 2025 |
Subject areas
- Technological subjects
Contact information
Course coordinator
Lecturers
- Gunnar René Øie
- Kirsti Elisabeth Berntsen
- Melissa Yuting Yan
- Sattanathan Subramanian
- Thomas Brox Røst
Department with academic responsibility
Department of Computer Science