TDT4127 - Programming and Numerics


Examination arrangement

Examination arrangement: Home examination
Grade: Letters

Evaluation form Weighting Duration Examination aids Grade deviation
Home examination 100/100 4 hours A

Course content

The course consists of two parts: Introduction to procedure-oriented programming in Python (2/3) and Numerics (1/3). The Python skills will be generally applicable to many different problems, but as soon as the level is high enough, most of the examples will be directed towards problem-solving in the Numerics domain.

Procedure-oriented programming:
- Variables and data types.
- Input and output.
- Control structures: Sequence, conditional program flow and repetitions.
- Structuring and modularisation of programs; functions and modules.
- Data structures: Lists, tables, text strings, sets, tuples and dictionaries.
- Persistent storage of data, file input and output, and exceptions.
- Recursion.
- Python as a programming environment.
- Computation of N-dimensional matrixes
- Plot of functions.

- Numeric Integration of Functions: Trapezoidal rule, Simpson's rule, Adaptive Simpson's rule
- Newton's method for finding zeros of a real-valued function
- Gaussian elimination for solving systems of linear equations
- Numerical solution of ordinary differential equations
- Fixed-point iteration

Learning outcome

By the end of the course, the candidate can
- explain central concepts and mechanisms of procedural programming.
- derive the result of small programs and functions
- explain number representation, precision of calculations, and the workings of central numerical methods

By the end of the course, the candidate can
- use relevant tools for editing and running Python code
- use viable data structures, control structures and decomposition in functions and modules to make well-structured, working code
- apply some central numerical methods to solve calculation problems, and import and use numerical library functions in Python
- identify causes for errors and lack of precision in programs, and correct the errors

Learning methods and activities

Lectures, exercise lectures, mandatory exercises.

Compulsory assignments

  • Exercises

Further on evaluation

The home exam will only be given in english; students can answer in norwegian.
For the continuation exam, home exam may be changed to oral exam

Specific conditions

Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.

Required previous knowledge

Mathematics similar required to attend the two year sivile engineering master program.

Course materials

Announced at the start of semester.

Credit reductions

Course code Reduction From To
TDT4109 5.0 01.09.2019
TDT4105 5.0 01.09.2019
TDT4110 5.0 01.09.2019
More on the course

Version: 1
Credits:  7.5 SP
Study level: Second degree level


Term no.: 1
Teaching semester:  AUTUMN 2020

No.of lecture hours: 3
Lab hours: 8
No.of specialization hours: 1

Term no.: 1
Teaching semester:  SPRING 2021

No.of lecture hours: 3
Lab hours: 8
No.of specialization hours: 1

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Numerical Mathematics
  • Numerical Mathematics
  • Technological subjects
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Computer Science



Examination arrangement: Home examination

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Autumn ORD Home examination 100/100 A

Release 2020-11-28

Submission 2020-11-28

Release 09:00

Submission 13:00

Room Building Number of candidates
Spring ORD Home examination 100/100 A INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

More on examinations at NTNU