PřF:Bi3011 Algorithms and programs - Course Information
Bi3011 Algorithmization and programmingFaculty of Science
- Extent and Intensity
- 2/2/0. 4 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- RNDr. Miroslav Kubásek, Ph.D. (lecturer)
doc. Ing. Daniel Schwarz, Ph.D. (lecturer)
- Guaranteed by
- doc. Ing. Daniel Schwarz, Ph.D.
RECETOX - Faculty of Science
Contact Person: RNDr. Miroslav Kubásek, Ph.D.
Supplier department: RECETOX - Faculty of Science
- Basic orientation in logic and formal languages.
- 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
- Course objectives
- The aim of the course is to provide students with basic concepts of programming and algorithmization using diagrams and examples in the chosen programming language (Java, Python).
- Learning outcomes
- After completion of the course, student will be able:
- to define basic data types and more complex data structures;
- to define appropriate data type to store a specific value;
- to design an algorithm to solve the assigned task and to document it using flow diagrams;
- to decompose a more complex algorithm into subprograms;
- to code the algorithm in a selected programming language and debug the program.
- 1. Introduction, history, definition of basic terms - algorithm, program, complexity.
- 2. Flow diagrams: definition, sequences, branching, cycles.
- 3. Addition, volume calculation, triangle, minimum search, quadratic equation, simple calculator.
- 4. Mean grade, prime numbers, factorial, sum of numerical series.
- 5. Cycles and examples, the number of characters in a file.
- 6. Subprograms: definition, parameters, return value, algorithm decomposition, basic sorting algorithms: selection sort, bubble sort.
- 7. Data types: ordinal, irregular, arrays, examples: reverse listing.
- 8. Recursion: definition, Fibonacci series - recursive vs. non-recursive solution, binary search - recursive vs. iterative.
- Buchalcevová, A.: Algoritmizace a programování. Praha: VŠE, 1994.
- Topfer, P.: Algoritmy a programovací techniky. Praha: Prometheus, 1995.
- Virius, M.: Základy algoritmizace. Praha: ČVUT, 1997.
- Teaching methods
- lectures, programming projects, homeworks
- Assessment methods
- 4 tasks in the course of the semester, final written test.
- Language of instruction
- Further Comments
- Study Materials
The course is taught annually.
The course is taught: every week.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/sci/spring2020/Bi3011