Introduction to Python programming

Garant předmětu:

Lecturer:

Jiří Fišer

Tutor:

Jiří Fišer

Supervisor:

Department of Software Engineering

Synopsis:

The aim of the course is to introduce students to programming in Python (version 3). First, students are introduced to the basic programming constructs in Python (conditions, cycles, functions). There is space dedicated to both the object and the functional paradigm. In the next part of the course, students are introduced to the use of Python in the field of scientific and technical calculations (NumPy, SciPy, SymPy libraries) and in the field of GUI application development or data processing (database).

Requirements:

Elementary knowledge of any programming language is recommended

Syllabus of lectures:

1) Python usage and properties, Python in interactive console and scripting in Python

2) Conditions, loops, functions

3) Lists, dictionaries, iterators

4) Input and output in Python, File and Directory Access

5-6) OOP in Python (introduction to OOP, classes, properties, methods)

7) Functional programming in Python (map, zip, lambda expression,…)

8-9) Introduction to NumPy, SciPy (ndarray, broadcasting, vectorization), data vizualization

10) GUI programming, PyQt, Kivy libraries

11) Data export, XML and JSON

12) SQL databases in Python

Syllabus of tutorials:

Study Objective:

Acquired knowledge: Students learn basic Python programming (version 3). Students are oriented both in the area of object and functional paradigm in Python.

Acquired skills: Students are able to use Python in scientific and technical computation (NumPy, SciPy, SymPy), as well as in the development of GUI applications or databases.

Study materials:

Key references:

[1] SUMMERFIELD, Mark. Python 3: výukový kurz. Brno: Computer Press, 2010. ISBN 978-80-251-2737-7.

[2] PILGRIM, Mark. Ponořme se do Python(u) 3: Dive into Python 3. Praha: Cz.Nic, c2010. CZ.NIC. ISBN 978-80-904248-2-1.

[3] ELKNER, Jeffrey, Allen B. DOWNEY, Chris MEYER a Jaroslav KUBIAS. Učíme se programovat v jazyce Python 3: How to think like a computer scientist - Learning with Python [online]. [cit. 2018-02-02]. Dostupné z: http://howto.py.cz

Recommended references:

[4] GUTTAG, John. Introduction to computation and programming using Python: with application to understanding data. Second edition. Cambridge, Massachusetts: The MIT Press, 2016. ISBN 978-0262529624.

Note:

Time-table for winter semester 2023/2024:

Time-table is not available yet

Time-table for summer semester 2023/2024:

Time-table is not available yet

The course is a part of the following study plans:

• Applications of Informatics in Natural Sciences (compulsory course in the program)