PřF:MDA204 Introduction to Python - Informace o předmětu
MDA204 Introduction to Python
Přírodovědecká fakultajaro 2025
- Rozsah
- 0/0/0. 6 kr. Ukončení: z.
- Vyučující
- Mgr. Tomáš Foltýnek, Ph.D. (přednášející)
- Garance
- Mgr. Tomáš Foltýnek, Ph.D.
Ústav matematiky a statistiky – Ústavy – Přírodovědecká fakulta
Dodavatelské pracoviště: Katedra strojového učení a zpracování dat – Fakulta informatiky - Předpoklady
- There are no specific requirements to enrol on the course, but the content presumes previous programming experience at least on a basic level.
- Omezení zápisu do předmětu
- Předmět je otevřen studentům libovolného oboru.
- Cíle předmětu
- The aim of the course is to provide students with an introduction to the Python programming language with a focus on data analytics. The students will learn how to write Python programs to solve real-world data analytics problems. They will also understand the fundamentals of object-oriented programming and how it can be applied to data analytics. Finally, the students will develop skills in data cleaning, data wrangling, data analysis, and data visualization using Python.
- Výstupy z učení
- After successful completion of the course, students will:
- have gained proficiency in Python programming;
- understand OOP concepts;
- have gained practical skills in using standard Python libraries for data cleaning, data wrangling, data analysis, and data visualization - Osnova
- 1. Introduction to Python (Installing Python, Basic syntax and data types, Variables and expressions, Control structures (if-else, loops), Functions and modules)
- 2. Object-Oriented Programming (Classes and objects, Inheritance and polymorphism, Encapsulation and data hiding, Abstraction and interfaces)
- 3. Data Cleaning and Preparation with Python(Reading and writing data in various formats (CSV, JSON, etc.), Data types and data structures, Handling missing values, Data transformation and manipulation)
- 4. Data Analysis with Python (Data analysis libraries (NumPy, Pandas, Matplotlib), Data exploration and visualization, Basic statistical analysis)
- 5. Data Wrangling with Python (Advanced data transformation and manipulation, Merging and joining datasets, Grouping and aggregating data)
- Literatura
- povinná literatura
- MCKINNEY, Wes. Python for data analysis : data wrangling with pandas, NumPy and Jupyter. Third edition. Sebastopol, CA: O'Reilly Media, 2022, xvi, 561. ISBN 9781098104030. info
- VANDERPLAS, Jacob T. Python data science handbook : essential tools for working with data. First edition. Tokyo: O'Reilly, 2017, xvi, 529. ISBN 9781491912058. info
- doporučená literatura
- SWEIGART, Albert. Automate the boring stuff with Python : practical programming for total beginners. 2nd edition. San Francisco: No Starch Press, 2020, xxxix, 547. ISBN 9781593279929. info
- GUZDIAL, Mark a Barbara ERICSON. Introduction to computing & programming in Python : a multimedia approach. 2nd ed. Upper Saddle River [N.J.]: Prentice Hall, 2010, xxiii, 401. ISBN 9780136060239. info
- ZELLE, John M. Python programming : an introduction to computer science. Wilsonville: Franklin, Beedle &Associates, 2004, xiv, 514. ISBN 1887902996. info
- Výukové metody
- Pre-recorded lectures and task assignments, synchronous consultations, asynchronous discussions, individual homework, individual project, and project presentation.
- Metody hodnocení
- The final mark will be composed of:
30% regular homework,
30% individual practical project + presentation,
40% final supervised written exam (theoretical + practical)
For the successful completion of the course, at least 60% points of each part are required. - Vyučovací jazyk
- Angličtina
- Permalink: https://is.muni.cz/predmet/sci/jaro2025/MDA204