Data Analysis and Computational Thinking
Computational thinking with algorithms, Python, Excel, data analysis, testing, and reliable programs
Beginner course | 3 EC | 7 modules
Learn to turn an unclear problem into a computational solution that another person can inspect, test, and improve.
Beginner level No programming prerequisite
Python The reference programming language
Excel Tabular analysis, checking, and communication
7 modules One cumulative learning path
What this course covers
DACT combines computational thinking, Excel data analysis, and Python programming. You will define problems, design algorithms, work with tabular data, write and test programs, and explain the assumptions and limits of your results.
The course moves from problem formulation and algorithm design through Excel and Python to records, files, simulation, testing, and reliable programs. The underlying ideas transfer to other domains, languages, and computational tools.
Modules
Computational thinking and algorithm design
Formulate computational problems and design, trace, test, and improve algorithms before programming.
Excel for data analysis
Structure, calculate with, refresh, summarize, and communicate changing tabular data.
Python foundations
Translate algorithms into Python programs and explain their values, calculations, and changing state.
Functions and decisions
Build reusable behaviour and explicit decision rules.
Sequences and loops
Build a reproducible minimum viable simulation and inspect its results in Excel.
Records and files
Represent, validate, process, and export persistent records.
Building Reliable Programs
Validate, test, and improve a complete simulation-based solution.
Where to go next
University of Twente students can find Canvas, the timetable, and the materials released for the current week in the enrolled-student guide.
For course outcomes, assessment, workload, and policies, consult the 2026–2027 syllabus. Independent learners can follow the course learning guide.