PřF:C2184 Introduction to programming in - Course Information
C2184 Introduction to programming in Python
Faculty of ScienceAutumn 2020
- Extent and Intensity
- 0/2/0. 2 credit(s) (plus 1 for the colloquium). Type of Completion: k (colloquium).
- Teacher(s)
- Mgr. et Mgr. Adam Midlik, Ph.D. (lecturer)
RNDr. Tomáš Raček, Ph.D. (lecturer)
doc. RNDr. Radka Svobodová, Ph.D. (lecturer)
Mgr. Václav Hejret (assistant)
RNDr. Ondřej Schindler, Ph.D. (assistant) - Guaranteed by
- prof. RNDr. Jaroslav Koča, DrSc.
National Centre for Biomolecular Research – Faculty of Science
Supplier department: National Centre for Biomolecular Research – Faculty of Science - Timetable of Seminar Groups
- C2184/01: Wed 17:00–18:50 prace doma
- Prerequisites
- 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
- Bioinformatics (programme PřF, B-BIC)
- 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, he/she will be able to process life science data with Python.
- Syllabus
- 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.
- Literature
- 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
- Online lectures. Individual solving of assigned exercises, discussions via the Discussion forum. Online consultations with the seminar tutor.
- Assessment methods
- mandatory homework assignments, two practical tests
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
- Enrolment Statistics (Autumn 2020, recent)
- Permalink: https://is.muni.cz/course/sci/autumn2020/C2184