Computational Programming with Python
Beräkningsprogrammering med Python

NUMA01F, 7.5 högskolepoäng

Gäller från och med: Autumn 2018
Beslutad av: Professor Thomas Johansson
Datum för fastställande: 2018-11-15

Allmänna uppgifter

Avdelning: Mathematics
Kurstyp: Gemensam kurs, avancerad nivå och forskarnivå
Kursen ges även på avancerad nivå med kurskod: NUMA01
Undervisningsspråk: English

Syfte

The aim of the the course is to give an introduction to computational programming in Python for postgraduate students without previous programming knowledge. Python is a modern scripting language with strong ties to Scientific Computing.

Mål

Kunskap och förståelse

För godkänd kurs skall doktoranden

• be able to explain and use basic programming concepts, data structures, conditional statements.
• be able do describe the structure of a Python program.

Färdighet och förmåga

För godkänd kurs skall doktoranden

• be able to convert algorithms into programming code
• be able to visualise, interpret and critically assess numerical results
• be able to report solutions to problems and numerical results in speech, writing and graphic form
• be able to use appropriate terminology in a logical and well-structured manner
• be able organise, implement and orally present a major programming project in carried out in group.

Värderingsförmåga och förhållningssätt

För godkänd kurs skall doktoranden be able to critically analyse the programs produced by fellow students and assess alternatives to his or her own programming solutions

Kursinnehåll

Basic programming concepts, data structures, conditional statements, functions and classes. Problem-solving using a few basic numerical methods associated with mathematics and physics. The basic functions and data types of the Python programming language: arithmetic operations, arrays of vectors, matrices, graphics functions, lists, tuples, dictionaries, file management. Use of modules such as NumPy, SciPy and Matplotlib The representation of floating point numbers and their implications for arithmetic Syntax: [for], [if-else], [while], list comprehensions, generators Nested functions, self-defined functions and modules Classes and inheritance applied to mathematical objects Tests and profiling

Kurslitteratur

Fuhrer, C., Solem, J. & Verdier, O.: Scientific Computing with Python 3 - Second Edition. 2016. ISBN 9781786463517.

Kursens undervisningsformer

Undervisningsformer: Föreläsningar, övningar, projekt

Kursens examination

Examinationsform: övrigt. Reports on programming exercises during the course, and a major programming project to be completed in groups.
Betygsskala: Underkänd, godkänd
Examinator:

Antagningsuppgifter

Urvalskriterier: Arrival time for application. At most five phd students.

Kurstillfällesinformation

Kontaktinformation och övrigt

Kursansvariga:
Hemsida: http://www.ctr.maths.lu.se/course/NUMA01/