A course is the basic teaching unit, it's design as a medium for a student to acquire comprehensive knowledge and skills indispensable in the given field. A course guarantor is responsible for the factual content of the course.
For each course, there is a department responsible for the course organisation. A person responsible for timetabling for a given department sets a time schedule of teaching and for each class, s/he assigns an instructor and/or an examiner.
Expected time consumption of the course is expressed by a course attribute extent of teaching. For example, extent = 2 +2 indicates two teaching hours of lectures and two teaching hours of seminar (lab) per week.
At the end of each semester, the course instructor has to evaluate the extent to which a student has acquired the expected knowledge and skills. The type of this evaluation is indicated by the attribute completion. So, a course can be completed by just an assessment ('pouze zápočet'), by a graded assessment ('klasifikovaný zápočet'), or by just an examination ('pouze zkouška') or by an assessment and examination ('zápočet a zkouška') .
The difficulty of a given course is evaluated by the amount of ECTS credits.
The course is in session (cf. teaching is going on) during a semester. Each course is offered either in the winter ('zimní') or summer ('letní') semester of an academic year. Exceptionally, a course might be offered in both semesters.
The subject matter of a course is described in various texts.
BI-PYT.21 Python Programming Extent of teaching: 3C Instructor: Completion: KZ Department: 18102 Credits: 5 Semester: Z,L Annotation:
The aim of the course is to get acquainted with basic efficient control and data structures of the Python programming language for text and binary data processing. The differences between philosophy of programming in Python and in other programming languages will be explained. Each topic is prepared for students in the format of a Jupyter notebook, which enables greater accent to individual student work. Before each lab, students pass a short test on the last week topic. Four homeworks plus a semester work will be assigned during the semester.
Lecture syllabus:
There are not any lectures.Seminar syllabus:
1. Introduction to Python. Virtual enviroment. Python syntax and semantics. 2. Built-in types. Operators. Conditions, Loops. 3. Lists, Tuples, Sets, Dictionaries. Slicing. Comprehensions. 4. Functions, Annotations, Decorators. 5. Generators, Iterators, Classes 6. File system, Command line arguments. 7. Modules, Packages 8. Numpy: dimensions, shape, size, axis, rank. N-dimensional slicing. Broadcasting. Vectorization. 9. Graphics and Numpy. Convolution. 10. Pandas. Conditions, Group by, Order by, Merge and Joins. SQL vs. Pandas. 11. Streamlit and web mini-applications for data science. 12. Unit testing with pytest. Asserting. Fixtures. 13. Semestral project presentations. Literature:
1. McKinney W. : Python for Data Analysis (2nd Edition). O'Reilly, 2017. ISBN 978-1491957660. 2. Lutz M. : Learning Python. O'Reilly, 2013. ISBN 978-1-449-35573-9. 3. Necaise R. D. : Data Structures and Algorithms Using Python. John Wiley & Sons, 2011. ISBN 978-047061829. 4. Horstmann C.S., Necaise R.D. : Python for Everyone (2nd Edition). John Wiley & Sons, 2016. ISBN 978-1-119-18665-6. Requirements:
We expect to understand the git versioning system at the BI-GIT course level and knowledge of at least one another programming language (C, C++, Java) at the level of the BI-AG1 class.
Informace o předmětu a výukové materiály naleznete na https://courses.fit.cvut.cz/BI-PYT/
Na cvičení budou studenti potřebovat vlastní notebook (alespoň jedno cvičení v počítačové učebně zajištěno).
Na tento předmět navazuje v magisterském studiu předmět Pokročilý Python.The course is also part of the following Study plans:
Page updated 20. 4. 2024, semester: L/2023-4, L/2020-1, L/2022-3, L/2021-2, Z/2019-20, Z/2022-3, Z/2020-1, Z/2023-4, L/2019-20, Z/2021-2, Z/2024-5, Send comments to the content presented here to Administrator of study plans Design and implementation: J. Novák, I. Halaška