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|Lecture/Exercise | |Lecture/Exercise | ||

|Monday | |Monday | ||

− | | | + | |13:10 - 14:40 |

|M112 / MS Teams: FMFI-Mathematics for Cognitive Science | |M112 / MS Teams: FMFI-Mathematics for Cognitive Science | ||

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

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|Exercise/Lecture | |Exercise/Lecture | ||

|Thursday | |Thursday | ||

− | | | + | |14:50 - 16:20 |

|M112 / MS Teams: FMFI-Mathematics for Cognitive Science | |M112 / MS Teams: FMFI-Mathematics for Cognitive Science | ||

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

## Latest revision as of 09:53, 16 September 2021

# 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 | Monday | 13:10 - 14:40 | M112 / MS Teams: FMFI-Mathematics for Cognitive Science | Mária Slavíčková |

Exercise/Lecture | Thursday | 14:50 - 16:20 | M112 / MS Teams: FMFI-Mathematics for Cognitive Science | Mária Slavíčková |

## How to join the course

I'll add all students who sign up for this course in the AiS (Academic Information System). The MS Teams should send you a notification about it. The course will be held in hybrid form, which means: those who can attend it personally will be present in M112 (pavilion of Mathematics, 1st floor, close to the 1st staircase). Those, who cannot participate personally, can use the link in MS Teams. All materials will be in MS Teams (I'll explain it more in the 1st class).

## Syllabus

- Basics of mathematical analysis: functions, differential calculus
- Basics of linear algebra: matrices and vectors, operations
- Basics of probability: likely and not likely, unconditional and conditional probability
- Basics of propositional and predicate logic

## 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 2022
- goal: course output
- weight: 30%

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