DV1614 - Applied Programming in Python - Blekinge Institute of Technology

1. Descision

This course is established by Dean 2019-04-25. The course syllabus is approved by Head of Department of Computer Science 2024-04-09 and applies from 2024-04-09.

2. Entry requirements

Admission to the course requires completed courses or completed parts of courses in Programming equivalent to 7.5 credits.

3. Objective and content

3.1 Objective

The aim of the course is to provide students with knowledge of object-oriented programming in Python, partly to be able to pursue continued studies in computer science and partly to be able to execute general programming assignments in working life.

3.2 Content

Syntax and semantics for the Python programming language
Management of embedded data structures, such as strings, lists, tuples, dictionaries and sets
List comprehension
Coding guidelines, style, common practice, typing and documentation of code
Program structuring using classes and construction of new classes
Constructors/destructors, methods, instance variables, class variables, overloading, generators, decorators, class relations and inheritance, abstract base classes
Error management and exceptions
In- and output from/to streams and files, synchronous as well as asynchronous
Automated testing, including assert
Use of external libraries, such as pandas, numpy, plotly, maplotlib

4. Learning outcomes

The following learning outcomes are examined in the course:

4.1. Knowledge and understanding

understand and explain in detail different Python programs
explain in detail basic concepts and techniques within object-oriented programming, such as classes, class relations, overloading etc
account in detail for an object-oriented manner of solving problems in the Python language
explain and demonstrate the differences between synchronous and asynchronous behaviour in conjunction with in- and output of data to streams and files

4.2. Competence and skills

independently implement a well-structured object-oriented solution in Python, based on a problem description
implement fundamental abstract data types in Python,
use the standard library of Python and the most suitable external libraries for a set assignment
implement well-documented self-testing Python programs

4.3. Judgement and approach

independently and critically evaluate and analyse their own solutions

5. Learning activities

The course is taught on campus and includes lectures and laboratory sessions. The lectures present theories and contribute to the theoretical understanding required to complete the course. The laboratory sessions apply the theories on practical components conducted individually and/or in groups.
Students are expected to possess, or acquire, the ability to independently seek information to solve problems and difficulties that arise.

6. Assessment and grading

Modes of examinations of the course

Code	Module	Credit	Grade
2410	Laboratory Session 1	1.5 credits	GU
2420	Laboratory Session 2	3.5 credits	GU
2430	On-campus Examination	2.5 credits	GU

The course will be graded G Pass, UX Failed result, a little more work required, U Fail.

The information before the start of the course states the assessment criteria and make explicit in which modes of examination that the learning outcomes are assessed.

An examiner can, after consulting the Disability Advisor at BTH, decide on a customized examination form for a student with a long-term disability to be provided with an examination equivalent to one given to a student who is not disabled.

7. Course evaluation

The course evaluation should be carried out in line with BTH:s course evaluation template and process.

8. Restrictions regarding degree

The course can form part of a degree but not together with another course the content of which completely or partly corresponds with the contents of this course.

9. Course literature and other materials of instruction

A Beginners Guide to Python 3 Programming
John Hunt
Publisher: Springer Nature Switzerland AG
Release Date: August 2019
ISBN: 9783030202897

The book is available in digital form in the BTH library.

Learning Python, 5th Edition
Mark Lutz
Publisher: O'Reilly Media, Inc.
Release Date: June 2013
ISBN: 9781449355739

Material from the department.

Reference: