Display language
To modulepage Generate PDF

#40787 / #2

SS 2017 - WiSe 2021/22

English

Programming Course and Project

6

Sprekeler, Henning

unbenotet

Portfolioprüfung

Zugehörigkeit


Fakultät IV

Institut für Softwaretechnik und Theoretische Informatik

34352100 FG Modellierung kognitiver Prozesse

No information

Kontakt


MAR 5-3

Velenosi, Lisa Alexandria

graduateprograms@bccn-berlin.de

Learning Outcomes

At the end of the course, students will be able to: - write complex computer programs - apply basic as well as advanced concepts of a modern programming language, (e.g., imperative and object oriented programming) and the basics of using design patterns - use tools for successful project management (version control tools, bug tracking, etc.) - develop a larger program in collaboration with other students – including the necessary specifications, documentation and test The course puts strong emphasis on the use of online resources and self-guided learning in order to teach the students how to acquire skills in a novel programming language using manuals and available resources.

Content

- using the UNIX operating system: basic commands, editor, navigation - using a repository (subversion) for version control during code development - introduction to the programming language python - objects and object attributes in python - object oriented programming in python - integrated development environments - test driven code development - extreme programming - refactoring - project management - design patterns

Module Components

Pflichtgruppe:

All Courses are mandatory.

Course NameTypeNumberCycleLanguageSWSVZ
Programming Course and ProjectPJSoSeEnglish3
Programming Course and ProjectIVSoSeEnglish3

Workload and Credit Points

Programming Course and Project (PJ):

Workload descriptionMultiplierHoursTotal
Präsenzzeit15.03.0h45.0h
Vor-/Nachbereitung15.03.0h45.0h
90.0h(~3 LP)

Programming Course and Project (IV):

Workload descriptionMultiplierHoursTotal
Präsenzzeit15.03.0h45.0h
Vor-/Nachbereitung15.03.0h45.0h
90.0h(~3 LP)
The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

IV: As a block before Semester Start Background knowledge and the principal concepts of the employed programming language are presented to the class by a lecturer. In order to integrate any specialist knowledge that some of the students in the interdisciplinary Computational Neuroscience Program may have, some topics may also introduced by individual students in seminar-style talks. Groups of up to 20 participants are taught the relevant practical details to complete programming exercises on the computer. They solve small programming tasks, partially in class, partially as homework. Project: Larger programming projects are solved in collaboration with other students (in groups of ca. 4-6), including students taking different roles within those projects, using project management tools and learning to effectively lead such projects. The different projects are individually supervised by the tutor.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

No information

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

ungraded

Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte insgesamt

Language

English

Test elements

NamePointsCategorieDuration/Extent
(Deliverable assessment) Assiguments during the IV50written3 h
(Deliverable assessment) Completition and Presentation of the project50oral30 min

Grading scale

At least 50 points in total needed to pass.

Test description (Module completion)

To pass the Module 60 Pts are required.

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Sommersemester.

Maximum Number of Participants

The maximum capacity of students is 20.

Registration Procedures

Enrollment to the module is handled in the first class of each module component (cf. 3). Students must be present in person. The module components Programming Course (lecture with exercises) and Project (lecture with exercises) have to be taken successively. Students of the Master program in Computational Neuroscience have to register with the examination office (Prüfungsamt) of TU Berlin before the first study achievement (homework assignment). For students from other programs, other regulations may apply. Please consult the examination regulations (Prüfungsordnung) of your program.

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable

 

Electronical lecture notes

Availability:  unavailable

 

Literature

Recommended literature
01. Pilgrim, Dive into Python, Springer-Verlag, 2004.
02. Lutz, Programming Python, O’Reilly, 2006.
03. Lutz and Ascher, Learning Python (Help for Programmers), O’Reilly, 2008.
04. Hetland, Beginning Python, Apress, 2008.
05. Martelli, Ravenscroft and Ascher, Python Cookbook, O’Reilly, 2005.
multiple online resources found on the courses web-page.

Assigned Degree Programs


This module is used in the following Degree Programs (new System):

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
This module is not used in any degree program.

Miscellaneous

No information