TU Delft
Year
NEDERLANDSENGLISH
Organization
Education Type
Education print this page print this page     
2016/2017 Technology, Policy and Management Master Engineering and Policy Analysis
EPA1333
Computer Engineering for Scientific Computing
ECTS: 5
Module Manager
Name E-mail
Dr. M.A. Oey    M.A.Oey@tudelft.nl
Responsible for assignments
Name E-mail
Dr. M.A. Oey    M.A.Oey@tudelft.nl
Co-responsible for assignments
Name E-mail
Dr. M.E. Warnier    M.E.Warnier@tudelft.nl
Contact Hours / Week x/x/x/x
4/0/0/0
Education Period
1
Start Education
1
Exam Period
1
2
Course Language
English
Course Contents
This course offers an introduction to scientific computing: programmatically modelling problems and analysing data. It will use Python and a number of tools and libraries often used for scientific computing. The course provides a mix of theory and skills which are practised using lab assignments (using Python) and discusses the following subjects:
- Programming: basic programming in Python.
- Algorithms and computing complexity
- Scientific computation with libraries such as Pandas, SciPy, NumPy
- Visualization with libraries such as matplotlib
- Other programming tools and topics (when time permits), such as Jupyter, source control management, debugging, data representation (XML, JSON), SQL, GUI, simulation, etc.
Study Goals
After taking the module the student will be able to:

translate a problem into an algorithm
read and explain relatively complex computer programs, written in Python
design and write relatively complex computer programs, written in Python that:
- read and parse data from a data source (file, web, database)
- transform, process and analyze that data
- visualize the results
- output the results in a file, webpage, database.
debug a python program
design, write and share code in a team, using source control management
Education Method
Mix of theory lectures, supervised practical lab sessions, and unsupervised online lectures/tutorials. Reading material will be available. Programming assignments will be given which are used to practice the programming skills and will be worked on during the practical lab sessions and in home-work assignments. One or more practical assignments will be graded and will count for the final mark. 4 contact hours per week.
Assessment
The final grade has two components:
- A grade (70%) for a written exam at the end that will contain open/closed questions and assignments. The questions will test the ability of the student to read and explain code and algorithms. The assignments will test the ability of the student to write and debug python programs that read, transform, process, analyse, and visualise data and write the results.
- A grade (30%) for one or more practical group assignments.

Both grades must be sufficient (>= 5.8) to pass. The group assignments can be made by small groups of students (2-3 students, but the size will depend on the total number of participants in the course).