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{{CourseHeader
 
{{CourseHeader
     | code = 2-IKV-102
+
     | 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
|Tuesday
+
|Monday
|11:30
+
|13:10 - 14:40
|M-112
+
|M112 / MS Teams: FMFI-Mathematics for Cognitive Science
|[[Martina Koronci Babinska|Martina Koronci Babinská]]
+
|[https://sluzby.fmph.uniba.sk/ludia/slavickova1 Mária Slavíčková]
 
|-
 
|-
|Excercise
+
|Exercise/Lecture
 
|Thursday
 
|Thursday
|09:50
+
|14:50 - 16:20
|M-112
+
|M112 / MS Teams: FMFI-Mathematics for Cognitive Science
|[[Martina Koronci Babinska|Martina Koronci Babinská]]
+
|[https://sluzby.fmph.uniba.sk/ludia/slavickova1 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 ==
 
== Syllabus ==
 
+
<ol>
{| class="alternative table-responsive"
+
<li>Basics of mathematical analysis: functions, differential calculus</li>
!Date
+
<li>Basics of linear algebra: matrices and vectors, operations </li>
!Topic
+
<li>Basics of probability: likely and not likely, unconditional and conditional probability </li>
!References
+
<li>Basics of propositional and predicate logic </li>
|-
+
</ol>
|03.10.
+
|Introduction. The basics of logic and proving methods: propositional logic.
+
|Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.
+
Rose-Hulman Institute of Technology: Pearson, 2004; [http://ceiucaweb.com.ar/documentos/6-informatica/3er-anio-2do-cuatri/estructura-de-datos/apunte/Discrete_and_Combinatorial_Mathematics_5th_ed_-_R._Grimaldi.pdf Download here]; chap. 2.1, 2.2
+
 
+
|-
+
|05.10.
+
|Introduction. The basics of logic and proving methods: predicate logic.
+
|Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.
+
Rose-Hulman Institute of Technology: Pearson, 2004; [http://ceiucaweb.com.ar/documentos/6-informatica/3er-anio-2do-cuatri/estructura-de-datos/apunte/Discrete_and_Combinatorial_Mathematics_5th_ed_-_R._Grimaldi.pdf Download here]; chap. 2.4, 2.5, 2.6
+
 
+
|}
+
 
+
 
+
== Homework ==
+
 
+
{| class="alternative table-responsive"
+
!Date
+
!Homework
+
!Points
+
!References
+
|-
+
|05.10.
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|Choose 2 Excercises from the Excercise 2.1 (page 54).
+
| 1 point / excercise
+
|Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.
+
Rose-Hulman Institute of Technology: Pearson, 2004; [http://ceiucaweb.com.ar/documentos/6-informatica/3er-anio-2do-cuatri/estructura-de-datos/apunte/Discrete_and_Combinatorial_Mathematics_5th_ed_-_R._Grimaldi.pdf Download here];
+
|}
+
  
 
== References ==
 
== References ==
  
* Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.
+
* Discrete structures with contemporary applications / Stanoyevitch A. CRC Press, Taylor & Francis Group, 2011.
Rose-Hulman Institute of Technology: Pearson, 2004. [http://ceiucaweb.com.ar/documentos/6-informatica/3er-anio-2do-cuatri/estructura-de-datos/apunte/Discrete_and_Combinatorial_Mathematics_5th_ed_-_R._Grimaldi.pdf Download here];
+
* A First Course in Real Analysis. Second Edition. / Protter, M.H. & Morrey, C.B. Springer-Verlag , 1991.
* Calculus / Gilbert Strang. Massachusetts Institute of Technology: Wellesley-Cambridge Press. [https://ocw.mit.edu/ans7870/resources/Strang/Edited/Calculus/Calculus.pdf Download here];
+
* Basics of Mathematical Functions: https://www.khanacademy.org/math/algebra/algebra-functions
* Fundamentals of Linear Algebra / James B. Carrell. Canada: University of British Colombia, 2005. [https://www.math.ubc.ca/~carrell/NB.pdf Download here];
+
* [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. [http://dai.fmph.uniba.sk/courses/ICI/russell-norvig.AI-modern-approach.3rd-ed.2010.pdf Download here];
+
* [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>
 
+
PROJECT 
+
* form: essay, presentation, song or movie
+
* topic: What does mathematics mean for me? What am I expecting from this course?
+
* term: 27.10.2017
+
* goal: self-study motivation
+
* weight: 15%
+
  
WEEKLY EXAMS
+
====THREE EXAM TESTS:====
*form: 10-15 minutes writing tests
+
*form: 60 minutes writing test
*term: every Thursday at the beginning of the exercise
+
*terms: to be announced
*goal: regular preparation
+
*goal: progress definition
*weight: 40%
+
*weight: 20 % each
*note: student can also achieve extra (bonus) points for: weekly homeworks, class work (solving problems and schoolmate’s help) and/or self-activity (lecture preparation… )
+
  
<b>OVERALL GRADING:</b> A > 90%, B > 80%, C> 70%, D > 60%, E > 52% points.
+
====ATTENDANCE, ACTIVITY====
 +
*form: classwork (solving problems and schoolmate’s help)
 +
*term: every lecture and exercise
 +
*goalregular preparation, cooperation, and virtual-social activity
 +
*weight: 10%
  
 +
====FINAL EXAM====
 +
*form: 90 minutes writing test
 +
*term: January, February 2022
 +
*goal: course output 
 +
*weight: 30%
  
  
== Information list ==
+
<b>OVERALL GRADING:</b>  A > 90%, B > 80%, C> 70%, D > 60%, E > 52%
{{Infolist|2-IKV-102|Course information sheet >}}
+

Latest revision as of 09:53, 16 September 2021

Mathematics for Cognitive Science 2-IKVa-102

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

  1. Basics of mathematical analysis: functions, differential calculus
  2. Basics of linear algebra: matrices and vectors, operations
  3. Basics of probability: likely and not likely, unconditional and conditional probability
  4. 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%