PV248 Python
Faculty of InformaticsAutumn 2019
- Extent and Intensity
- 1/1. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- RNDr. Petr Ročkai, Ph.D. (lecturer)
RNDr. Petr Ročkai, Ph.D. (seminar tutor)
Mgr. Zuzana Baranová (assistant)
Mgr. Lukáš Korenčik (assistant) - Guaranteed by
- RNDr. Petr Ročkai, Ph.D.
Department of Computer Systems and Communications – Faculty of Informatics
Supplier department: Department of Computer Systems and Communications – Faculty of Informatics - Timetable
- each odd Thursday 12:00–13:50 A217
- Timetable of Seminar Groups:
PV248/01: each odd Thursday 14:00–15:50 B130, P. Ročkai
PV248/02: each odd Thursday 16:00–17:50 B130, P. Ročkai - Prerequisites
- Basic programming skills in Python (at least to the extent covered in IB111).
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 60 student(s).
Current registration and enrolment status: enrolled: 0/60, only registered: 0/60, only registered with preference (fields directly associated with the programme): 0/60 - fields of study / plans the course is directly associated with
- Image Processing and Analysis (programme FI, N-VIZ)
- Applied Informatics (programme FI, N-AP)
- Bioinformatics and systems biology (programme FI, N-UIZD)
- Bioinformatics (programme FI, N-AP)
- Computer Games Development (programme FI, N-VIZ_A)
- Computer Graphics and Visualisation (programme FI, N-VIZ_A)
- Computer Networks and Communications (programme FI, N-PSKB_A)
- Cybersecurity Management (programme FI, N-RSSS_A)
- Formal analysis of computer systems (programme FI, N-TEI)
- Graphic design (programme FI, N-VIZ)
- Graphic Design (programme FI, N-VIZ_A)
- Hardware Systems (programme FI, N-PSKB_A)
- Hardware systems (programme FI, N-PSKB)
- Image Processing and Analysis (programme FI, N-VIZ_A)
- Information security (programme FI, N-PSKB)
- Information Security (programme FI, N-PSKB_A)
- Quantum and Other Nonclassical Computational Models (programme FI, N-TEI)
- Computer graphics and visualisation (programme FI, N-VIZ)
- Computer Networks and Communications (programme FI, N-PSKB)
- Principles of programming languages (programme FI, N-TEI)
- Cybersecurity management (programme FI, N-RSSS)
- Services development management (programme FI, N-RSSS)
- Software Systems Development Management (programme FI, N-RSSS)
- Services Development Management (programme FI, N-RSSS_A)
- Service Science, Management and Engineering (eng.) (programme FI, N-AP)
- Service Science, Management and Engineering (programme FI, N-AP)
- Software Systems Development Management (programme FI, N-RSSS_A)
- Software Systems (programme FI, N-PSKB_A)
- Software systems (programme FI, N-PSKB)
- Machine learning and artificial intelligence (programme FI, N-UIZD)
- Teacher of Informatics and IT administrator (programme FI, N-UCI)
- Informatics for secondary school teachers (programme FI, N-UCI) (2)
- Artificial Intelligence and Natural Language Processing (programme FI, B-IN)
- Artificial Intelligence and Natural Language Processing (programme FI, N-IN)
- Computer Games Development (programme FI, N-VIZ)
- Processing and analysis of large-scale data (programme FI, N-UIZD)
- Natural language processing (programme FI, N-UIZD)
- Course objectives
- The goal of this subject is to teach students the specifics of programming in Python, mainly on with practical exercises. During the semester, students will work on programming assignments, which will focus on the material covered in the lectures.
By the end of the course, students will:
* understand the basics of object-oriented design and implementation in Python
* be acquainted with the standard library
* understand the basics of problem decomposition and robust implementation - Learning outcomes
- Student will be able to:
- program in the Python programming language
- understand Python code written by others
- find and use the information needed for Python development
- test their programs written in Python - Syllabus
- 1. Introduction, text, regular expressions
- 2. Objects and classes
- 3. Testing and debugging
- 4. Persistent data
- 5. Working with numeric data
- 6. Memory and data model
- 7. Lambda, iteration, decorators
- 8. Lexical closures, carcasses
- 9. Modules and packages
- 10. Concurrency, exceptions
- 11. Communication, HTTP
- 12. Asyncio Library
- Literature
- recommended literature
- LUTZ, Mark. Programming Python. 4th ed. Sebastopol, California: O'Reilly, 2010, 1632 pp. info
- Teaching methods
- exercises, homework, projects
- Assessment methods
- activity in exercises, homework evaluation, and project
- Language of instruction
- English
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (Autumn 2019, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2019/PV248