Course detail

Programming and Algorithms 2

FEKT-BPC-PP2Acad. year: 2022/2023

Algorithms in MATLAB. Introduction to Python. Basic data types and statements. Algorithms in Python: transcript of selected MATLAB routines. Advanced data types (sets, collections). Creating and calling functions. Local and recursive functions, control structures and functions. Modules and packages. Files operations. Object-oriented programming. Graphical user’s interface. Examples of applications.

Language of instruction

Czech

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

prof. Dr. Ing. Zbyněk Raida

Department

Department of Radio Electronics (UREL)

Learning outcomes of the course unit

Obtaining basic programming abilities and algorithmic thinking. Understanding fundamentals of Python.

Prerequisites

The subject knowledge on the secondary school level is required.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

Evaluated computer exercises: 10 x 3 = 30 points. Tests during semester: 2 x 10 = 20 points. Individual project in Python: 50 points.

Course curriculum

01. Python: basic data types and statements. Algorithms: sorting, golden cut.
02. Algorithms: local and global optimization.
03. Python: advanced data types. Algorithms: string operations I.
04. Python: functions. Algorithms: string operations II.
05. Algorithms: numerical integration, numerical conversions.
06. Python: tuples and files. Algorithms: file operations.
07. Algorithms: filter design. Individual projects.
08. TEST I.
09. Python: modules and packages. Algorithms: module and package operations.
10. Python: object-oriented programming.
11. Python: graphical user’s interface.
12. TEST II.

Work placements

Not applicable.

Aims

To educate students in algorithmic and programming thinking. To explain basic properties and structures of Python language.

Specification of controlled education, way of implementation and compensation for absences

The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

BEAZLEY, D., JONES B.K. Python Cookbook, 3/E. Sebastopol (Canada): O’ Reilly Media, 2013. ISBN: 978-1-449-34037-7 (CS)
LUTZ, M. Learning Python, 5/E. Sebastopol (Canada): O’ Reilly Media, 2013. ISBN: 978-1-449-35573-9 (CS)

Recommended reading

Not applicable.

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme BPC-ECT Bachelor's 2 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

prof. Dr. Ing. Zbyněk Raida

Syllabus

1. Algorithmization (extensions of basic knowledge from the previous semester). Definition of the task, the definition of inputs / outputs, expressing
an algorithm in meta-language, rewritting into programming language.
2. Introduction to C language. Basic types of variables, derived types, constants, arrays.
3. Expressions, arithmetic conversions, arithmetic operators, shift operators, relation operators, logical operators, bitwise operators, assignment
operators, operator priority.
4. Strings and their operators, library functions, standard library string.h.
5. Commands, compound statements, branching commands, cycles and control commands. Flowchart.
6. Function. Declaration of functions, methods of function calling, treatment events, recursion of functions.
7. Advanced data types. Union, enum, dynamic variable, pointer.
8. Objects. Lexical elements, constants and strings, classes, objects, object types.
9. User interface of Microsoft Visual C++ Studio. Graphical components.
10. Algorithms I. Finding maxima and minima, sorting.
11. Algorithms II. Programming with arrays, matrices operations.
12. Algorithms III. Programming with files in Windows.
13. Algorithms IV. Database systems. Records, sorting, searching, statistics. Linking of databases.

Exercise in computer lab

26 hod., compulsory

Teacher / Lecturer

prof. Dr. Ing. Zbyněk Raida

Syllabus

1. Algorithmization (extensions of basic knowledge from the previous semester). Definition of the task, the definition of inputs / outputs, expressing
an algorithm in meta-language, rewritting into programming language.
2. Introduction to C language. Basic types of variables, derived types, constants, arrays.
3. Expressions, arithmetic conversions, arithmetic operators, shift operators, relation operators, logical operators, bitwise operators, assignment
operators, operator priority.
4. Strings and their operators, library functions, standard library string.h.
5. Commands, compound statements, branching commands, cycles and control commands. Flowchart.
6. Function. Declaration of functions, methods of function calling, treatment events, recursion of functions.
7. Advanced data types. Union, enum, dynamic variable, pointer.
8. Objects. Lexical elements, constants and strings, classes, objects, object types.
9. User interface of Microsoft Visual C++ Studio. Graphical components.
10. Algorithms I. Finding maxima and minima, sorting.
11. Algorithms II. Programming with arrays, matrices operations.
12. Algorithms III. Programming with files in Windows.
13. Algorithms IV. Database systems. Records, sorting, searching, statistics. Linking of databases.

Elearning

eLearning: currently opened course