C2184 Introduction to programming in Python

Faculty of Science
Autumn 2024
Extent and Intensity
0/2/0. 2 credit(s) (plus 1 for the colloquium). Type of Completion: k (colloquium).
RNDr. Ondřej Schindler, Ph.D. (lecturer)
RNDr. Tomáš Raček, Ph.D. (lecturer)
Mgr. Bc. Jana Porubská (seminar tutor)
Mgr. Bc. Gabriela Bučeková (seminar tutor)
Lukáš Bohuš (assistant)
Guaranteed by
RNDr. Tomáš Raček, Ph.D.
National Centre for Biomolecular Research – Faculty of Science
Supplier department: National Centre for Biomolecular Research – Faculty of Science
Computer basics, advantage knowledge of UNIX.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course provides an introduction into programing in Python language. The course is focused on its practical usage, especially demo applications in life sciences (problem solving, data processing). After finishing of the course, the students will be able to use basic syntactic constructions in Python (e.g., conditions, cycles, functions, basic data types). Furthermore, the students can create simple programs in Python and they can use Python as a tool for processing of data, obtained in their research and educative projects.
Learning outcomes
After finishing of the course, the student will be able to program in Python. Specifically, they will be able to process life science data with Python.
  • Introduction - basic features of Python, cmparison with other programming languages, why and when to use Python. Introduction to Python development environment.
  • Basic constructions of the language: basic data types, logic and mathematics operators, conditions, cycles. Inputs and outputs.
  • Advanced data types - strings and collections (tuples, lists, dictionaries). Functions, lambda functions and recursion.
  • Basics about complexity and algoritmization. Examples of basic algorithms. highest common divisor, prime numbers.
  • Further examples of algorihtms: sorting algorithms, searching. Errors, exceptions and their processing.
  • Work with files. Processing of binary files and text files.
  • Introduction to OPP, objects. Moduls and packages.
  • Work with text, introduction into regular expressions and processing of XML/JSON.
  • Application of external modules in life sciences.
    recommended literature
  • SUMMERFIELD, Mark. Python 3 : výukový kurz. Translated by Lukáš Krejčí. Vydání 1. Brno: Computer Press, 2010, 584 stran. ISBN 9788025127377. info
    not specified
  • MCKINNEY, Wes. Python for data analysis : [agile tools for real world data]. 1st ed. Sebastopol, Calif.: O'Reilly, 2013, xiii, 452. ISBN 9781449319793. info
Teaching methods
Lectures and class exercises, homework assignments.
Assessment methods
Mandatory homework assignments, two practical tests.
Language of instruction
Follow-Up Courses
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Autumn 2011 - acreditation, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, autumn 2021, Autumn 2022, Autumn 2023.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2024/C2184