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{{CourseHeader | {{CourseHeader | ||

− | | code = 2- | + | | code = 2-IKVa-102 |

− | | title = Mathematics | + | | title = Mathematics for Cognitive Science |

}} | }} | ||

__TOC__ | __TOC__ | ||

− | The lectures will provide students with basics of propositional and | + | The lectures will provide students with the basics of propositional and |

− | predicate logic, linear algebra, mathematical analysis, and probability that are important for | + | predicate logic, linear algebra, mathematical analysis, and the probability that are important for |

the study of informatics and its role in (computational) cognitive science. At the same time, | the study of informatics and its role in (computational) cognitive science. At the same time, | ||

students will learn about mathematical culture, notation, way of thinking and expressing | students will learn about mathematical culture, notation, way of thinking and expressing | ||

Line 19: | Line 19: | ||

!Lecturer | !Lecturer | ||

|- | |- | ||

− | |Lecture | + | |Lecture/Exercise |

− | | | + | |Wednesday |

− | | | + | |14:00 - 15:30 |

− | | | + | |MS Teams: FMFI-Mathematics for Cognitive Science |

− | |[ | + | |[https://sluzby.fmph.uniba.sk/ludia/slavickova1 Mária Slavíčková] |

|- | |- | ||

− | | | + | |Exercise/Lecture |

− | | | + | |Wednesday |

− | | | + | |15:45 - 17:15 |

− | | | + | |MS Teams: FMFI-Mathematics for Cognitive Science |

− | |[ | + | |[https://sluzby.fmph.uniba.sk/ludia/slavickova1 Mária Slavíčková] |

|} | |} | ||

+ | |||

+ | ==How to join the course== | ||

+ | I'll use your e-mail addresses from the Academic Information System (AiS) and I add you to the course. You should find an e-mail concerning the first meeting, please, accept it (no later than 21.9.2020, if not, first check the spam. If you'll not be successful, send me an e-mail). As a student at Comenius University, you have access to MS Office 365 for free. If you are a student on mobility without access to MS Office 365, you can join the lectures via the web. | ||

== Syllabus == | == Syllabus == | ||

− | + | <ol> | |

− | + | <li>Basics of logic and proving methods: propositional logic, predicate logic, the sets of numbers, proofs. </li> | |

− | + | <li>Basics of mathematical analysis: functions, differential calculus</li> | |

− | + | <li>Basics of linear algebra: matrices and vectors, operations.Looking forward to meeting you in the lessons </li> | |

− | + | <li>Basics of probability: likely and not likely, unconditional and conditional probability </li> | |

− | + | </ol> | |

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== References == | == References == | ||

− | * Discrete | + | * Discrete structures with contemporary applications / Stanoyevitch A. CRC Press, Taylor & Francis Group, 2011. |

− | + | * A First Course in Real Analysis. Second Edition. / Protter, M.H. & Morrey, C.B. Springer-Verlag , 1991. | |

− | + | * Basics of Mathematical Functions: https://www.khanacademy.org/math/algebra/algebra-functions | |

− | + | * [https://ocw.mit.edu/ans7870/resources/Strang/Edited/Calculus/Calculus.pdf Calculus] / Gilbert Strang. Massachusetts Institute of Technology: Wellesley-Cambridge Press. | |

− | * Artificial Intelligence: A Modern Approach / Stuart Russell and Peter Norvig. The USA: Pearson, 2010. | + | * [https://www.math.ubc.ca/~carrell/NB.pdf Fundamentals of Linear Algebra] / James B. Carrell. Canada: University of British Colombia, 2005. |

+ | * Artificial Intelligence: A Modern Approach / Stuart Russell and Peter Norvig. The USA: Pearson, 2010. | ||

== Course grading == | == Course grading == | ||

− | To be classified student has to achieve at least 50% of every activity: | + | <b>To be classified student has to achieve at least 50% of every activity:</b> |

− | + | ||

− | + | ====THREE EXAM TESTS:==== | |

− | * | + | *form: 60 minutes writing test |

− | * | + | *terms: to be announced |

− | * goal: | + | *goal: progress definition |

− | * weight: | + | *weight: 20 % each |

− | + | ====ATTENDANCE, ACTIVITY==== | |

− | *form: | + | *form: classwork (solving problems and schoolmate’s help) |

− | *term: every | + | *term: every lecture and exercise |

− | *goal: regular preparation | + | *goal: regular preparation, cooperation, and virtual-social activity |

− | + | *weight: 10% | |

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− | * | + | |

+ | ====FINAL EXAM==== | ||

+ | *form: 90 minutes writing test | ||

+ | *term: January, February 2021 | ||

+ | *goal: course output | ||

+ | *weight: 30% | ||

− | + | <b>OVERALL GRADING:</b> A > 90%, B > 80%, C> 70%, D > 60%, E > 52% points. | |

− | + |

## Revision as of 19:01, 16 September 2020

# Mathematics for Cognitive Science 2-IKVa-102

## Contents

The lectures will provide students with the basics of propositional and predicate logic, linear algebra, mathematical analysis, and the probability that are important for the study of informatics and its role in (computational) cognitive science. At the same time, students will learn about mathematical culture, notation, way of thinking and expressing oneself.

## Course schedule

Type | Day | Time | Room | Lecturer |
---|---|---|---|---|

Lecture/Exercise | Wednesday | 14:00 - 15:30 | MS Teams: FMFI-Mathematics for Cognitive Science | Mária Slavíčková |

Exercise/Lecture | Wednesday | 15:45 - 17:15 | MS Teams: FMFI-Mathematics for Cognitive Science | Mária Slavíčková |

## How to join the course

I'll use your e-mail addresses from the Academic Information System (AiS) and I add you to the course. You should find an e-mail concerning the first meeting, please, accept it (no later than 21.9.2020, if not, first check the spam. If you'll not be successful, send me an e-mail). As a student at Comenius University, you have access to MS Office 365 for free. If you are a student on mobility without access to MS Office 365, you can join the lectures via the web.

## Syllabus

- Basics of logic and proving methods: propositional logic, predicate logic, the sets of numbers, proofs.
- Basics of mathematical analysis: functions, differential calculus
- Basics of linear algebra: matrices and vectors, operations.Looking forward to meeting you in the lessons
- Basics of probability: likely and not likely, unconditional and conditional probability

## References

- Discrete structures with contemporary applications / Stanoyevitch A. CRC Press, Taylor & Francis Group, 2011.
- A First Course in Real Analysis. Second Edition. / Protter, M.H. & Morrey, C.B. Springer-Verlag , 1991.
- Basics of Mathematical Functions: https://www.khanacademy.org/math/algebra/algebra-functions
- Calculus / Gilbert Strang. Massachusetts Institute of Technology: Wellesley-Cambridge Press.
- Fundamentals of Linear Algebra / James B. Carrell. Canada: University of British Colombia, 2005.
- Artificial Intelligence: A Modern Approach / Stuart Russell and Peter Norvig. The USA: Pearson, 2010.

## Course grading

**To be classified student has to achieve at least 50% of every activity:**

#### THREE EXAM TESTS:

- form: 60 minutes writing test
- terms: to be announced
- goal: progress definition
- weight: 20 % each

#### ATTENDANCE, ACTIVITY

- form: classwork (solving problems and schoolmate’s help)
- term: every lecture and exercise
- goal: regular preparation, cooperation, and virtual-social activity
- weight: 10%

#### FINAL EXAM

- form: 90 minutes writing test
- term: January, February 2021
- goal: course output
- weight: 30%

**OVERALL GRADING:** A > 90%, B > 80%, C> 70%, D > 60%, E > 52% points.