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Course info
KPV / PPVS
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Course description
Department/Unit / Abbreviation
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KPV
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PPVS
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Comp. Support in Mech. Engineering
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Form of course completion
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Pre-Exam Credit
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Form of course completion
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Pre-Exam Credit
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Accredited / Credits
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Yes,
4
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
2
[Hours/Week]
Tutorial
2
[Hours/Week]
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Course credit prior to examination
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No
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Course credit prior to examination
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No
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Included in study average
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NO
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Language of instruction
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Czech
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Occ/max
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Summer semester
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0 / -
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0 / -
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0 / -
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Included in study average
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NO
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Winter semester
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92 / -
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0 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter semester
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Semester taught
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Winter semester
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Minimum (B + C) students
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10
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
S|N |
Periodicity |
každý rok
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Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
Yes
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Fundamental theoretical course |
No
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Evaluation scale |
S|N |
Substituted course
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KPV/PPR2
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Preclusive courses
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KPV/PPVSA
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Prerequisite courses
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N/A
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Informally recommended courses
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KPV/TI or KPV/9TI
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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The course is intended to give students a good insight into the following areas:
Event driven programming, file and database processing, linear and non-linear general data structures and apply these knowledge to usage of data structures in mechanical engineering and algorithms of their processing.
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Requirements on student
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Conditions for obtaining credit:
- participation on seminars
- passing the tests
Examination requirements: The course is not completed with an exam, but the credit.
Detailed requirements are at coursware.
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Content
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Excel charts and formulas, pivot tables and charts. Introduction to data processing, formats and data processing, classical batch data processing, linear, tree and network data structures. Basics of database data processing. Data structures in engineering: order, BOM and process. Algorithms of data structures processing in mechanical engineering. Independent work in a simple database system. Basic SQL queries.
1. Basic concepts of database processing, functional, data and object analysis
2. Conceptual modeling, E-R-A diagram,
3. Database models, relational model, transformation of KS into RDB model, data normalization
4. SQL language, formulation of queries, SQL examples
5. Possibilities of database corruption (technical, program, user), multi-user access to data
6. Application of simulation in mechanical engineering - case studies
7. Application of visualization and virtual reality in mechanical engineering
8. Linear data structures, tree and network data structures
9. Basic data structures in engineering, BOM, procedure, order and algorithms for their processing - initiation
10. Basic data structures in engineering, BOM, procedure, order and algorithms for their processing - completion
11. Examples of data structures in various information systems
12. Information system Helios Orange and its use in logistics and production management
13. Credit test
Any changes in content and timing will be sent electronically.
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Activities
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Fields of study
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Guarantors and lecturers
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Guarantors:
Doc. Ing. Pavel Kopeček, CSc. (100%),
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Lecturer:
Doc. Ing. Petr Hořejší, Ph.D. ,
Doc. Ing. Pavel Kopeček, CSc. (100%),
Doc. Ing. Pavel Raška, Ph.D. (100%),
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Tutorial lecturer:
Doc. Ing. Petr Hořejší, Ph.D. (40%),
Doc. Ing. Pavel Kopeček, CSc. (25%),
Ing. Tomáš Macháč (100%),
Ing. Bc. Miroslav Malaga, Ph.D. (100%),
Doc. Ing. Pavel Raška, Ph.D. (35%),
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Literature
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Basic:
Ryant, Ivan. Algoritmy a datové struktury objektově. Vydání první. 2017. ISBN 978-80-270-1660-0.
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Basic:
Kroenke, David; Auer, David J. Databáze. 1. vydání. 2015. ISBN 978-80-251-4352-0.
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Basic:
Kopeček, Pavel. Modelování a algoritmizace datových struktur ve strojírenství. [Plzeň] : SmartMotion, 2013. ISBN 978-80-87539-50-7.
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Basic:
Kopeček, Pavel. Příklad v MS Access. [Plzeň] : SmartMotion, 2013. ISBN 978-80-87539-51-4.
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Basic:
Kopeček, Pavel; Holub, Vojtěch. Úvod do zpracování dat. [Plzeň] : SmartMotion, 2013. ISBN 978-80-87539-49-1.
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Extending:
Hernandez, Michael J.; Viescas, John. Myslíme v jazyku SQL : tvorba dotazů. Praha : Grada Publishing, 2004. ISBN 80-247-0899-X.
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Extending:
DeBarros Anthony. Practical SQL: A Beginner's Guide to Storytelling with Data. No Starch Press, 2018. ISBN 978-1593278274.
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Extending:
Oppel, Andrew J. SQL bez předchozích znalostí : [průvodce pro samouky]. Vyd. 1. Brno : Computer Press, 2008. ISBN 978-80-251-1707-1.
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Recommended:
Kruczek, Aleš. Microsoft Access 2010 : podrobná uživatelská příručka. Vyd. 1. Brno : Computer Press, 2010. ISBN 978-80-251-3289-0.
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On-line library catalogues
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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E-learning [dáno e-learningovým kurzem]
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10
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Preparation for formative assessments (2-20)
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12
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Contact hours
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52
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Preparation for comprehensive test (10-40)
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30
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Total
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104
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
understand what algorithmization is |
have basic knowledge of working with files |
master any procedural language of the 3rd generation |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
be able to work with MS Office tools (Word, Excel) |
be able to work with PC |
be able to write and debug a simple program application for working with files in a higher language |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
to know the basic concepts of database data processing |
to know what general linear and nonlinear data structures are |
to know what data structures in mechanical engineering (BOM, process, order) are |
to know the methods of determining the amount, cost and running time from data structures |
Skills - skills resulting from the course: |
perform data analysis of simple data processing tasks |
propose a simple database in MS ACCESS |
use SQL to work with databases |
work with macros in MS ACCESS |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Test |
Skills - skills achieved by taking this course are verified by the following means: |
Skills demonstration during practicum |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
E-learning |
Multimedia supported teaching |
Individual study |
One-to-One tutorial |
Interactive lecture |
Skills - the following training methods are used to achieve the required skills: |
Cooperative instruction |
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