1. komponenta

Lecture type	Total
Lectures	30
Laboratory exercises	30

* Load is given in academic hour (1 academic hour = 45 minutes)

Course objective:
Introduce students to the basics of programming and concepts of relational and statistical databases
Course implementation program
1. Introduction. Principles of programming
2. Basic of Matlab
3. Computer operation in a network environment.
4. Phyton programming language in engineering and science
5. SciPy, Numpy, Matplot Phyton library
6. Introduction to databases. Database management systems.
7. Data modeling process. Entity-relationship model: entities, relationships, attributes, keys.
8. Graphical representation of the Entity-relationship model. Entity modeling.
9. Relational data model. Relational algebra
10. Introduction to MS Access
11. Functional dependences and limitations of the relational model.
12. Normalization. Fundamentals of object model.
13. Transforming the E-R model into a relational model. Fundamentals of physical organization
14. Basics of database protection.
15. Statistical databases (data warehouses): purpose, basic concepts, multidimensional cube

General competencies:
Basic knowledge of programming. Basic knowledge in the design of relational databases and access and use of the scientific databases.

Special competencies:
Using Matlab and Phyton (SciPy, Numpy and MatPlot). Basics of using MS Access. Creation of a simpler database.

Obligations of students in teaching and ways of their execution students are required to attend lectures and laboratory exercises students are required to independently prepare 3 assignments and reports on laboratory exercises. Students are required to access knowledge tests and colloquia

Teaching methods: lectures (ex cathedra), laboratory exercises, consultations

Method of testing knowledge and taking exams:
Oral exam on laboratory exercises. Written reports made in laboratory exercises. 2 written tests (60% on each). The total grade consists of: 65% grade from written test, 25% grade from laboratory exercises and 10% attendance at lectures and homework.

Method of monitoring the quality and success of the course: Student survey

Course learning outcomes:
1. Students will be able to use the Matlab program in solving problems
2. students will be able to find procedural algorithm to solve simpler problems
3. Student will use Pyhton for simple calculations
4. explain the concept of database and database management system
4. explain the design of a relational database
5. Use MS Access as relational database
6. create a simple database in MS Access
7. Collect data from an online database

1. 1. Ž. Ban, J. Matuško, I. Petrović Primjena programskog sustava MATLAB za rješavanje tehničkih problema, Graphis, Zagreb, 2010.,
2. D. Grundler, T. Rolich, A. Hursa. MATLAB i primjena u tekstilnoj tehnologiji : Sveučilište u Zagrebu, Tekstilno-tehnološki fakultet,Zagreb, 2010.,
3. MATLAB, The Language of Technical Computing, The MathWorks, Inc., 20022005M. Varga, Baze podataka- Konceptualno, logičko i fizičko modeliranje podataka, Društvo za razvoj informacijske pismenosti (DRIP), Zagreb, 1994,
4. C.Allen, S.Chatwin, C.A. Creary, Introduction to Relational Databases and SQL Programming, McGraw-Hill, 2004,
5. C.N. Prague, M.R. Irwin., J. Reardon, Microsoft Office Access 2003 Bible, Wiley, 2004,
6. H.Garcia-Molina, J.D.Ullman, J.D.Widom, Database Systems: The Complete Book, Prentice-Hall, New Jersey, 2002,
7. T.Thai, H.Q.Lam, .NET Framework Essentials, 3rd edition, O Reilly & Associates, Sebastopol, 2003,
8. Introduction to Python for Science and Engineering, The aim of this book is to provide science and engineering students a practical introduction to technical programming in Python., David J. Pine, CRC Press, 2019.

Mandatory course - Regular studij - Environmental Engineering