PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2024
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Taught in person.
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Mon 10:00–11:50 C416
Prerequisites
PB016 Intro to AI || IV126 Fundamentals of AI || PV021 Neural Networks || PV056 ML and Data Mining
This course is given in English. Presentations and project documentation can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 53 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Learning outcomes
Students will be able to:
- design, analyze and elaborate a solution of a selected task in the field of artificial intelligence;
- present the selected step-by-step approach;
- justify the chosen implementation process;
- design an evaluation process of the created application and process its results.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
English
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/aiproject/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2023
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Taught in person.
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 16. 2. to Thu 11. 5. Thu 14:00–15:50 C416
Prerequisites
PB016 Intro to AI || IV126 Fundamentals of AI || PV021 Neural Networks || PV056 Machine Learning
This course is given in English. Presentations and project documentation can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 53 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Learning outcomes
Students will be able to:
- design, analyze and elaborate a solution of a selected task in the field of artificial intelligence;
- present the selected step-by-step approach;
- justify the chosen implementation process;
- design an evaluation process of the created application and process its results.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
English
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/aiproject/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2022
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Taught in person.
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 17. 2. to Thu 12. 5. Thu 14:00–15:50 C525
Prerequisites
PB016 Artificial Intelligence I || IV126 Artificial Intelligence II || PV021 Neural Networks || PV056 Machine Learning
This course is given in English. Presentations and project documentation can be in English, Czech or Slovak.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 52 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Learning outcomes
Students will be able to:
- design, analyze and elaborate a solution of a selected task in the field of artificial intelligence;
- present the selected step-by-step approach;
- justify the chosen implementation process;
- design an evaluation process of the created application and process its results.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
English
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2021
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Taught online.
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 12:00–13:50 Virtuální místnost
Prerequisites (in Czech)
PB016 Artificial Intelligence I
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 52 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Learning outcomes
Students will be able to:
- design, analyze and elaborate a solution of a selected task in the field of artificial intelligence;
- present the selected step-by-step approach;
- justify the chosen implementation process;
- design an evaluation process of the created application and process its results.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2020
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Mon 17. 2. to Fri 15. 5. Tue 12:00–13:50 B411
Prerequisites (in Czech)
PB016 Artificial Intelligence I
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 52 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Learning outcomes
Students will be able to:
- design, analyze and elaborate a solution of a selected task in the field of artificial intelligence;
- present the selected step-by-step approach;
- justify the chosen implementation process;
- design an evaluation process of the created application and process its results.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2019
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Fri 10:00–11:50 C416
Prerequisites (in Czech)
PB016 Artificial Intelligence I
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 23 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Learning outcomes
Students will be able to:
- design, analyze and elaborate a solution of a selected task in the field of artificial intelligence;
- present the selected step-by-step approach;
- justify the chosen implementation process;
- design an evaluation process of the created application and process its results.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2018
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 10:00–11:50 C416
Prerequisites (in Czech)
PB016 Artificial Intelligence I
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 23 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Learning outcomes
Students will be able to:
- design, analyze and elaborate a solution of a selected task in the field of artificial intelligence;
- present the selected step-by-step approach;
- justify the chosen implementation process;
- design an evaluation process of the created application and process its results.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2017
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 14:00–15:50 B411
Prerequisites (in Czech)
PB016 Artificial Intelligence I
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 23 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2016
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Wed 12:00–13:50 C416
Prerequisites (in Czech)
PB016 Artificial Intelligence I
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 23 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2015
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Thu 10:00–11:50 B411
Prerequisites (in Czech)
PB016 Artificial Intelligence I
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 22 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2014
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Mon 14:00–15:50 B411
Prerequisites (in Czech)
PB016 Introduction to AI
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 22 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2013
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Fri 10:00–11:50 C511
Prerequisites (in Czech)
PB016 Introduction to AI
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 22 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2012
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 12:00–13:50 C511
Prerequisites (in Czech)
PB016 Introduction to AI
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 22 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2011
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Prerequisites (in Czech)
PB016 Introduction to AI
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 21 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught: every week.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2010
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Timetable
Wed 11:00–12:50 B313
Prerequisites (in Czech)
PB016 Introduction to AI
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 21 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Teaching methods
Individual work on analysis and implementation of the project, preparation of documentation, with regular consultations with the lecturer.
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2009
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Timetable
Wed 12:00–13:50 C511
Prerequisites (in Czech)
PB016 Introduction to AI
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 18 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Assessment methods
Consultations during the project work. Presentation of the implemented project, creation of HTML documentation of the project (see examples at the course web page).
Language of instruction
Czech
Further Comments
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2008
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Timetable
Tue 10:00–11:50 C511
Prerequisites (in Czech)
PB016 Introduction to AI
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 18 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Assessment methods (in Czech)
Předvedení implementovaného projektu, vytvoření HTML stránek dokumentace projektu (viz příklady na webové stránce předmětu).
Language of instruction
Czech
Further Comments
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2007
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Timetable
Wed 12:00–13:50 B003
Prerequisites (in Czech)
! P026 Artificial Intelligence Project && PB016 Introduction to AI
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on individual project. The choice of programming language for the project is not limited, for recommended topics see PB016 Introduction to Artificial Intelligence.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Assessment methods (in Czech)
Předvedení implementovaného projektu, vytvoření HTML stránek dokumentace projektu (viz příklady na webové stránce předmětu).
Language of instruction
Czech
Further Comments
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2006
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Timetable
Wed 12:00–13:50 C525
Prerequisites (in Czech)
! P026 Artificial Intelligence Project && PB016 Introduction to AI
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on the project.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2005
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Aleš Horák, Ph.D. (lecturer)
Guaranteed by
prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Aleš Horák, Ph.D.
Timetable
Tue 8:00–9:50 B411
Prerequisites (in Czech)
! P026 Artificial Intelligence Project && PB016 Introduction to AI
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on the project.
Syllabus
  • Study of a chosen area of artificial intelligence
  • Project implementation.
Literature
  • Russell,Stuart J. and Norvig, Peter: Artificial intelligence :a modern approach, 2nd edition, Upper Saddle River : Prentice Hall, 2003.
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Assessment methods (in Czech)
Student si v průběhu semestru: - samostatně navrhne téma projektu, které konzultuje s přednášejícím; - zpracuje analýzu projektu a přednese o ní krátký referát; - implementuje projekt, v průběhu implementace konzultuje s přednášejícím; - ke konci semestru připraví dokumentaci k implementovanému projektu, přednese o něm referát a představí jej v chodu. Kladné hodnocení je uděleno za zdárný průběh tohoto postupu.
Language of instruction
Czech
Further Comments
The course is taught annually.
Teacher's information
http://nlp.fi.muni.cz/uiprojekt/
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2004
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Pavel Smrž, Ph.D. (lecturer)
Guaranteed by
prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Pavel Smrž, Ph.D.
Timetable
Tue 8:00–9:50 B411
Prerequisites (in Czech)
! P026 Artificial Intelligence Project
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on the project. It is possible to work in groups (2-4 students), the complexity of the project should be proportional to this number.
Syllabus
  • The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on the project. It is possible to work in groups (2-4 students), the complexity of the project should be proportional to this number.
Literature
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is also listed under the following terms Spring 2003, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.

PA026 Artificial Intelligence Project

Faculty of Informatics
Spring 2003
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Pavel Smrž, Ph.D. (lecturer)
Guaranteed by
prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. RNDr. Pavel Smrž, Ph.D.
Timetable
Tue 8:00–9:50 B411
Prerequisites (in Czech)
! P026 Artificial Intelligence Project
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on the project. It is possible to work in groups (2-4 students), the complexity of the project should be proportional to this number.
Syllabus
  • The aim of the seminar is to provide students with a deeper knowledge concerning a chosen area of artificial intelligence and practical checking of this knowledge by working on the project. It is possible to work in groups (2-4 students), the complexity of the project should be proportional to this number.
Literature
  • NILSSON, Nils J. Artificial intelligence :a new synthesis. San Francisco: Morgan Kaufmann Publishers. xxi, 513 s. ISBN 1-55860-535-5. 1998. info
  • NORVIG, Peter and Stuart Jonathan RUSSELL. Artificial intelligence :a modern approach. Upper Saddle River: Prentice Hall. xxviii, 93. ISBN 0-13-103805-2. 1995. info
  • COHEN, Paul R. Empirical methods for artificial intelligence. Cambridge: MIT Press. xvi, 404. ISBN 0262032252. 1995. info
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is also listed under the following terms Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.
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