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Lecturer(s)
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Nejedlová Dana, Ing. Ph.D.
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Course content
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Lecture 1. Computer representation of integer numbers. 2. Computer representation of real (floating-point) numbers and characters. 3. The concept of an algorithm. Ways to design effective algorithms. 4. Algorithm representation. 5. Efficiency of algorithms demonstrated on searching in a list. 6. Asymptotic analysis of algorithms demonstrated on sorting. 7. Polynomial and non-polynomial algorithms. Complexity of typical problems. 8. Polynomial, NP, NP-complete and NP-hard problems. 9. Implementation as a connection between HW and SW. 10. Programming languages. 11. Data structures. 12. Dynamic data structures. Files. 13. Recursive algorithms efficiency. 14. The most important information from students' papers selected for theoretical test in Computers II. Tutorials 1. MS Excel: formatting, series, lock, comments, hypertext links, formulas, graphs. 2. MS Excel: absolute and relative addressing in formulas, functions IF and VLOOKUP. 3. MS Excel: working with large lists, their sorting and filtering. 4. MS Excel: pivot (contingency) tables. 5. MS Excel: Goal Seek and Solver add-in applied to production planning and transport problem. 6. MS Excel: preparation for test. 7. MS Excel: test. 8. MS Word: styles, creation of large documents, sections. 9. MS Word: multilevel numbering of chapters, insertion of graphs, tables, equations, cross reference, table of contents. 10. MS Excel: solutions of various types of problems using Solver add-in. 11. MS Excel: data validation and conditional formatting. 12. MS Excel: matrix formulas, naming ranges. 13. MS Excel: dynamic contingency table and histogram using matrix formulas and Analysis ToolPak add-in. 14. MS Excel: function INDIRECT combined with matrix formulas.
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Learning activities and teaching methods
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Monological explanation (lecture, presentation,briefing), Working activities (workshops)
- Class attendance
- 56 hours per semester
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Learning outcomes
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The aim of the course is to improve analytical thinking and independent decision-making based on the information acquired and their ability to solve problems with computer support. Students are taught to create their own computer applications in any programming language. Algorithms, their structure, development and effectiveness are emphasized. Part of the course is run on Microsoft Office.
Students obtain knowledge in given course in accordance with requirements and course programme.
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Prerequisites
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Basic computer literacy Basic experience with word processor and spreadsheet
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Assessment methods and criteria
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Oral exam, Written exam, Essay, Systematické pozorování studenta, Oral presentation of self-study, Written assignment
Active participation in tutorials. 5 minute long or 2 page paper on computers-related topic. Test in spreadsheet MS Excel.
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Recommended literature
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BROOKSHEAR, G., BRYLOW, D. Computer Science: An Overview (12th Edition). Pearson, 2014. ISBN 978-0133760064.
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GÁLA, L., POUR, J., TOMAN, P. Podniková informatika. Grada, 2006. ISBN 80-247-1278-4.
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MAŘÍK, V., ŠTEPÁNKOVÁ, O., LAŽANSKÝ , J., kol. Umělá inteligence 3. díl. Academia Praha, 2003. ISBN 80-200-0472-6.
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STAIR, R., REYNOLDS, G. Principles of Information Systems (12th Edition). Course Technology, 2015. ISBN 978-1285867168.
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