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Lecturer(s)
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Kopeček Pavel, doc. Ing. CSc.
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Hořejší Petr, doc. Ing. Ph.D.
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Breit Petr, Mgr.
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Course content
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Introduction, data and information in CIM. Data structures: basic types of data structures and their operations, logical data structures (linear, tree, network, relational), SQL for working with relational databases, multi-user access (data sharing, locks, data protection), modes of database system operation (client, server), examples of DBS (MS SQL Server, Access), specifics of databases in mechanical engineering and economics, database design in engineering (data modeling, ER diagrams, transformation of ER diagrams into logical data structures). Data security. Utilization of artificial intelligence methods in the design, management, and use of database systems (AI-assisted modeling, SQL query generation, prompt engineering). Practice at the terminal/PC with a specific database system. 1. Introduction. Basic concepts. Data, information, and database systems. 2. Data structures. Objects. Components. 3. Building information systems using database technology. Conceptual modeling, functional and data modeling, conceptual and database schema. 4. Conceptual E-R model, data normalization. 5. Database models. Relational model - RDBS. Transformation of conceptual schema into RDBS. 6. Relational algebra. SQL. 7. Data structures in mechanical engineering and SQL (e.g., bill of materials). 8. AI and databases: Prompt engineering for information systems. How to properly formulate requirements for AI to design database structures, SQL queries, and documentation. Practical demonstrations. 9. Knowledge discovery in databases. Data mining in marketing. 10. Data organization. Multi-user access to data. Transactions, data locking. 11. Database system architecture (File-Server, Client-Server, Distributed databases, Application integration). 12. Object-relational, object-oriented, and special database systems. Databases on the web, XML databases. 13. Modern AI and databases: Using AI for SQL query generation, automated database modeling, ChatGPT as a database interface. Integration of AI into BI and ERP systems.
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Learning activities and teaching methods
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Lecture with practical applications, E-learning, One-to-One tutorial, Laboratory work, Individual study
- Contact hours
- 78 hours per semester
- Preparation for formative assessments (2-20)
- 20 hours per semester
- Preparation for an examination (30-60)
- 30 hours per semester
- Undergraduate study programme term essay (20-40)
- 30 hours per semester
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| prerequisite |
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| Knowledge |
|---|
| understand what algorithmization is |
| have basic knowledge of working with files |
| master any 3rd generation procedural language |
| understand what object-oriented programming technology is |
| Skills |
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| be able to work with MS Office tools (Word, Excel, Access) |
| control PC work |
| be able to write and debug a simple form program application in a higher language |
| be able to create simple SQL queries in Access |
| Competences |
|---|
| N/A |
| N/A |
| N/A |
| learning outcomes |
|---|
| Knowledge |
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| know what data warehouses, data markets, and what knowledge is |
| know the principle of electronic signature and data encryption |
| know methods of ensuring program reliability and data security |
| know the basic architectures of database management systems |
| know how AI can support working with databases (e.g., automatic SQL query generation, database structure design, intelligent assistants for DB use) |
| Skills |
|---|
| design data models based on data analysis |
| to implement a simple database system |
| create programs in C # environment with SQL server in the background |
| manipulate databases using SQL |
| use AI to generate SQL queries and optimize database operations and apply prompt engineering for the design of database structures |
| Competences |
|---|
| N/A |
| N/A |
| N/A |
| N/A |
| N/A |
| teaching methods |
|---|
| Knowledge |
|---|
| E-learning |
| Individual study |
| One-to-One tutorial |
| Interactive lecture |
| Skills |
|---|
| Laboratory work |
| Individual study |
| Competences |
|---|
| One-to-One tutorial |
| Interactive lecture |
| assessment methods |
|---|
| Knowledge |
|---|
| Combined exam |
| Test |
| Individual presentation at a seminar |
| Skills |
|---|
| Seminar work |
| Competences |
|---|
| Combined exam |
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Recommended literature
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Eugene Roberts. Hands-On SQL Databases and LLMs: A Complete Guide to Data Management and AI in Action. USA, 2025. ISBN 979-8286780938.
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Holub, Vojtěch; Kopeček, Pavel. Objektové myšlení a objektová analýza. [Plzeň] : SmartMotion, 2013. ISBN 978-80-87539-52-1.
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Lacko, Luboslav. Databáze: datové sklady, OLAP a dolování dat : s příklady v SQL Serveru a Oracle. Vyd. 1. Brno : Computer Press, 2003. ISBN 80-7226-969-0.
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Laurenčík, Marek. SQL : podrobný průvodce uživatele. Praha : Grada Publishing, 2018. ISBN 978-80-271-0774-2.
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Rauch, Jan; Šimůnek, Milan. Dobývání znalostí z databází, LISp-Miner a GUHA. Vydání první. 2014. ISBN 978-80-245-2033-9.
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Stanek, William R. Microsoft SQL Server 2012 : kapesní rádce administrátora. 1. vyd. Brno : Computer Press, 2013. ISBN 978-80-251-3797-0.
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Ulrych, Zdeněk. Databázové programování ve VB.NET. [Plzeň] : SmartMotion, 2013. ISBN 978-80-87539-48-4.
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