TNK128 · 6 credits · Basic level (G1N) · Datateknik
Fundamental Programming for Data Analytics
Active · next start HT 2026
64%
passed the latest regular sitting
DAT1 · 28 Oct 2025 · 22 students
72%
passed the regular sittings, all sittings over the last 5 years
DAT1 · 78 students
56%
Harder than 56% of courses at basic level
Compared with 874 courses at the same level, ordinary exams over the last three academic years. 58 students.
Part of 3 programmes
Other module
DAT1 Computer exam Python
- 5
- 4
- 3
- U
Main rounds
72% passed · 78 students
- 64%22
- 83%36
- 60%20
Later rounds
50% passed · 14 students
- 60%5
- 44%9
- Pass a later round: 50% (14 students), compared with 72% (78 students) on the ordinary exam
- Get 4 or 5: 37% (92 students)
Show small sittings (5)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 50%2
- 0%1
- 50%2
- 100%2
- 50%4
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
LAB1 Laboratory work in Python
- G
Main rounds
100% passed · 78 students
- 100%21
- 100%37
- 100%20
Later rounds
No sittings with at least 5 students.
Show small sittings (1)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
Hand-in or lab
LAB2 Laboratory work in Matlab
- G
Main rounds
100% passed · 70 students
- 100%18
- 100%36
- 100%16
Later rounds
No sittings with at least 5 students.
Show small sittings (3)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%3
- 100%1
- 100%4
About the course
Aim
In this course, you will learn how to use programming for problem solving and analysis of data.
After completing the course, the student should be able to:
- Write scripts for data analysis using Python
- Use basic data structures for problem solving in Python
- Apply tools available in some commonly used Python packages
- Generalize programming skills in Python to other script languages, specifically Matlab
Content
- Introduction to different types of programming paradigms and languages
- Python basics: programming environment and documentation, program flow, variables, comments, numerical operators, loops, conditional statements
- Python data structures and looping techniques: tuples, lists, dictionaries, sets, iterators, and generators
- Python standard libraries and essential third-party packages for data manipulation, numerical computing, and visualization
- Debugging of code
- Data retrieval from various sources, such as json files, csv files, html files, XML files, databases or APIs
- Introduction to Matlab programming and toolboxes
- Examiner
- Nils Breyer
- Scheduled hours
- 48 h
- Main field of study
- Datateknik