ECTS - PWSZ im. Witelona w Legnicy

ECTS - PWSZ im. Witelona w Legnicy ECTS - PWSZ im. Witelona w Legnicy

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The Witelon University of Applied Sciences in Legnica - Field: Management and production engineering ECTS credits 5 1. Course title Methods of Artificial Intelligence 2. Course contents Lecture Introduction to computational intelligence; Methods of knowledge representation; Decision making on the basis of logical knowledge representation; Decision making on the basis of knowledge representation with uncertainty (probabilistic and fuzzy approach); Artificial neural networks; Combining classifiers; Methods of improving quality and stabilizing classifier (boosting, bagging); Introduction into machine learning and its taxonomy; Inductive learning; Evaluating hypotheses Seminar During seminar student present chosen topics connected with artificial intelligence and its practical implementations, e.g. how to work selected machine learning methods. 3. Prerequisites none 4. Learning outcomes Students learn about methods of decision making and they will be able to solve real decision problems using described methods. 5. Recommended reading 1. Bishop Ch. M., Pattern Recognition and Machine Learning, Springer 2006. 2. Duda R.O., Hart P.E., Stork D.G., Pattern Classification, Morgan Kaufmann, 2001. 3. Alpaydin E., Introduction to Machine Learning, 2nd Edition, MIT Press, 2010. 6. Type of course optional 7. Teaching team Department of Computer Systems and Applied Informatics 8. Course structure Form Number of hours Semester Year Lecture Classes Laboratory Project 30/12 VII 4 Seminar Other 30/18 VII 4 Total student’s workload 150 9. Assessment methods Positive mark seminar and written test are the conditions of ranking the lecture 10. Language of instruction Polish ECTS Course Catalogue 2010/2011 1194

The Witelon University of Applied Sciences in Legnica - Field: Management and production engineering Subjects for speciality: Industrial safety engineering ECTS credits 3 1. Course title Safety and rescue systems. 2. Course contents Lecture Analysis of safety systems in Poland. Extraordinary. Emergency response plans. The phases of crisis management. Progressive Management. Conservative management. Levels of response. Studies and plans to spatial development in Poland. Security domain. Civil planning. Civil defense. Definitions of the crisis. Public perception of risks. The role of the security system. The organization and functioning of security services. The organization and working methods of security services and health. Civil-Military Cooperation. Tools and computer information systems design safety. The organization of information, warning and alarm Classes The analysis of the incident. Rules of conduct for rescue. Rescue in Poland and abroad. Levels of directing rescue action. Assisting decision-making. Spatial information systems. Rescue and environmental, chemical, technical and medical. National Rescue-Extinguishing System. National Medical Rescue. Fighting fires, technical failures and natural disasters. The role and tasks of public administration, services and inspection and fire rescue system. Cooperation between institutions. The role of voluntary organizations and NGOs in rescue operations. Humanitarian Aid Organization. 3. Prerequisites none 4. Learning outcomes The student has knowledge of the organization and operation of safety systems and rescue, as well as methods and techniques to detect, identify and measure risks. The student has skills in security systems and security systems to organize and rescue. The student has the practical application of methods in the face of threats and accidents. The student has a sense of responsibility for the quality of aid, as well as the appropriate ethical attitude in the emergency action taken. 5. Recommended reading 1. Zarządzanie kryzysowe, obrona cywilna kraju, ochrona informacji niejawnych, S. Mazur, F.R. Krynojewski, G. Mikrut, P. Tchorzewski, AWF, 2003. 2. Istota inżynierii systemów zarządzania bezpieczeństwem, E. Kołodziński, (http://www.uwm.edu.pl/rci/publikacje/Istota_inzynierii_systemow.pdf ) 3. Zagrożenia bezpieczeństwa i organizacja przeciwdziałania ich skutkom, E. Kołodziński, (http://www.uwm.edu.pl/rci/publikacje/bezpieczenstwo9.pdf ) 4. Sensory do monitorowania zagrożeń bezpieczeństwa cywilnego, Z. Mierczyk, (http://www.uwm.edu.pl/rci/publikacje/Szczecin_2_2006.pdf ) 5. Ustawa z dnia 8 września 2006 r. o Państwowym Ratownictwie Medycznym ( Dz.U. z 20.10.2006 r. Nr 191, poz. 1410). 6. Type of course Obligatory 7. Teaching team Faculty of Medicine 8. Course structure Form Number of hours Semester Year Lecture 30/12 IV 2 Classes Laboratory Project Seminar Other 15/12 IV 2 Total student’s workload 90 9. Assessment methods Lecture – pass with grade, classes – pass with grade 10. Language of instruction Polish ECTS Course Catalogue 2010/2011 1195

The Witelon University of Applied Sciences in Legnica - Field: Management and production engineering<br />

<strong>ECTS</strong> credits<br />

5<br />

1. Course title<br />

Methods of Artificial Intelligence<br />

2. Course contents<br />

Lecture<br />

Introduction to computational intelligence; Methods of knowledge representation; Decision making on the basis of<br />

logical knowledge representation; Decision making on the basis of knowledge representation with uncertainty<br />

(probabilistic and fuzzy approach); Artificial neural networks; Combining classifiers; Methods of <strong>im</strong>proving quality and<br />

stabilizing classifier (boosting, bagging); Introduction into machine learning and its taxonomy; Inductive learning;<br />

Evaluating hypotheses<br />

Seminar<br />

During seminar student present chosen topics connected with artificial intelligence and its practical <strong>im</strong>plementations,<br />

e.g. how to work selected machine learning methods.<br />

3. Prerequisites<br />

none<br />

4. Learning outcomes<br />

Students learn about methods of decision making and they will be able to solve real decision problems using described<br />

methods.<br />

5. Recommended reading<br />

1. Bishop Ch. M., Pattern Recognition and Machine Learning, Springer 2006.<br />

2. Duda R.O., Hart P.E., Stork D.G., Pattern Classification, Morgan Kaufmann, 2001.<br />

3. Alpaydin E., Introduction to Machine Learning, 2nd Edition, MIT Press, 2010.<br />

6. Type of course<br />

optional<br />

7. Teaching team<br />

Department of Computer Systems and Applied Informatics<br />

8. Course structure<br />

Form Number of hours Semester Year<br />

Lecture<br />

Classes<br />

Laboratory<br />

Project<br />

30/12 VII 4<br />

Seminar<br />

Other<br />

30/18 VII 4<br />

Total student’s workload 150<br />

9. Assessment methods<br />

Positive mark seminar and written test are the conditions of ranking the lecture<br />

10. Language of instruction<br />

Polish<br />

<strong>ECTS</strong> Course Catalogue 2010/2011<br />

1194

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