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     | title = Fundamentals of Programming
 
     | title = Fundamentals of Programming
 
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{{Infolist|2-IKV-105|Course information sheet}}
 
  
 
__TOC__
 
__TOC__
  
This course teaches the students the basics of programming using Python programming language. It focuses on fundamental concepts of programming like for example if statements, while cycle, for cycle, variables etc. This course also puts emphasis on concepts useful for students of cognitive science including numerical computations using NumPy, visualizations or basics of machine learning techniques using artificial neural networks.
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The course provides students with the basics of programming and algorithmic thinking using Python programming language. It focuses on elements of programming (variables, if-statement, for-loop, etc.) and writing simple programs. Additionally it introduces concepts from computer science useful for students of cognitive science. It puts emphasis on the ability to intrinsically understand existing source code and make use of Python libraries, including the famous scientific libraries such as NumPy for numerical computations on data matrices and MatPlotLib for plotting. If time allows, the finale of the course comprises very light introduction to machine learning including the well-known scientific libraries (SciKitLearn, Pytorch).
  
== Course schedule ==
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== Basic info ==
 
{| class="alternative table-responsive"
 
{| class="alternative table-responsive"
 
!Type
 
!Type
Riadok 19: Riadok 17:
 
|-
 
|-
 
|Lecture
 
|Lecture
|Monday
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|Wednesday
|10:40
+
|14:00 - 15:30
|MS Teams
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|I-9 or [https://teams.microsoft.com/l/team/19%3anPeT3IYFHoQ2vhVx_n981yUDjwfhtSB_73ze--oy-F01%40thread.tacv2/conversations?groupId=c49dd56c-ddcf-4423-ba2c-7163988b39a2&tenantId=ce31478d-6e7a-4ce7-8670-a5b9d51884f9 MS Teams: 2-IKV-105 CogProg]
 
|[[Kristina Malinovska|Kristína Malinovská]]
 
|[[Kristina Malinovska|Kristína Malinovská]]
 
|-
 
|-
 
|Labs
 
|Labs
|Monday
+
|Wednesday
|12:20
+
|15:40 - 17:10
|MS Teams
+
|I-9 or [https://teams.microsoft.com/l/team/19%3anPeT3IYFHoQ2vhVx_n981yUDjwfhtSB_73ze--oy-F01%40thread.tacv2/conversations?groupId=c49dd56c-ddcf-4423-ba2c-7163988b39a2&tenantId=ce31478d-6e7a-4ce7-8670-a5b9d51884f9 MS Teams: 2-IKV-105 CogProg]
|[[Kristina Malinovska|Kristína Malinovská]]
+
|[[Matej Fandl|Matej Fandl]]
 
|}
 
|}
  
== Syllabus ==
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== Indicative Course Schedule ==
 
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{| class="alternative table-responsive"
 
{| class="alternative table-responsive"
 +
!#
 
!Date
 
!Date
 
!Topic
 
!Topic
 
|-
 
|-
|21.09.
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|1.
|Organization and Introduction. Interactive shell, console input/output, expressions, variables.
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|29.09.  
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| Introduction: what is programming? Basic concepts
 
|-
 
|-
|28.09.
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|2.
|
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|06.10.
 +
| Variables, basic types, console input/output, my first program
 
|-
 
|-
|05.10.
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|3.
|If statements, lists, strings, logic.
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|13.10.
 +
| Control flow: if, for, lists, strings and formatting
 
|-
 
|-
|12.10.
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|4.
|While cycle, for cycle, list comprehensions.
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|20.10.
 +
| Control flow: if, for, lists, strings and formatting
 
|-
 
|-
|19.10.
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|5.
|Dictionaries, sets, objects.
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|27.10.
 +
| Writing programs: functions and modules, values vs. references
 
|-
 
|-
|26.10.
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|6.
|Functions, arguments and scopes.
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|03.11.
 +
| Collections (list, tuple, set, dictionary), working with files
 
|-
 
|-
|02.11.
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|7.
|TBA
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|10.11.
 +
| Exceptions, working with files and directories
 
|-
 
|-
|09.11.
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|8.
|TBA
+
|17.11.
 +
| *State holiday*
 
|-
 
|-
|16.11.
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|9.
|TBA
+
|24.11.
 +
| Object-oriented programming, trees, *recursion
 
|-
 
|-
|23.11.
+
|10.
|TBA
+
|01.12.
 +
| Numpy. and Matplotlib
 
|-
 
|-
|30.11.
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|11.
|TBA
+
|08.12.
 +
| Machine Learning and ANN: basics and libraries
 
|-
 
|-
|7.12.
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|12.
|TBA
+
|15.12.
|-
+
| Project
|14.12.
+
|TBA
+
 
|}
 
|}
 +
 +
== Syllabus ==
 +
* Introduction: what is programming? Basic concepts
 +
* Variables, basic types, console input/output, my first program
 +
* Control flow: if, for, lists, strings and formatting
 +
* Writing programs: functions and modules, values vs. references
 +
* Collections (list, tuple, set, dictionary), working with files
 +
* Exceptions, working with files and directories
 +
* Object-oriented programming, trees, *recursion
 +
* Numpy. and Matplotlib
 +
* Machine Learning and ANN: basics and libraries
  
 
== Course grading ==
 
== Course grading ==
  
* Labs activity and participation (max. 20 points, 2 points for every excersise, -0.5 points for absence).
+
* Weekly homework (max. 20 points).
 
* Final project (max. 30 points).
 
* Final project (max. 30 points).
 +
* Bonus assignments.
 
* <b>Overall grading:</b> A (50-46), B (45-41), C (40-36), D (35-31), E (30-26), Fx (25-0).
 
* <b>Overall grading:</b> A (50-46), B (45-41), C (40-36), D (35-31), E (30-26), Fx (25-0).

Verzia zo dňa a času 18:57, 27. september 2021

Fundamentals of Programming 2-IKV-105

The course provides students with the basics of programming and algorithmic thinking using Python programming language. It focuses on elements of programming (variables, if-statement, for-loop, etc.) and writing simple programs. Additionally it introduces concepts from computer science useful for students of cognitive science. It puts emphasis on the ability to intrinsically understand existing source code and make use of Python libraries, including the famous scientific libraries such as NumPy for numerical computations on data matrices and MatPlotLib for plotting. If time allows, the finale of the course comprises very light introduction to machine learning including the well-known scientific libraries (SciKitLearn, Pytorch).

Basic info

Type Day Time Room Lecturer
Lecture Wednesday 14:00 - 15:30 I-9 or MS Teams: 2-IKV-105 CogProg Kristína Malinovská
Labs Wednesday 15:40 - 17:10 I-9 or MS Teams: 2-IKV-105 CogProg Matej Fandl

Indicative Course Schedule

# Date Topic
1. 29.09. Introduction: what is programming? Basic concepts
2. 06.10. Variables, basic types, console input/output, my first program
3. 13.10. Control flow: if, for, lists, strings and formatting
4. 20.10. Control flow: if, for, lists, strings and formatting
5. 27.10. Writing programs: functions and modules, values vs. references
6. 03.11. Collections (list, tuple, set, dictionary), working with files
7. 10.11. Exceptions, working with files and directories
8. 17.11. *State holiday*
9. 24.11. Object-oriented programming, trees, *recursion
10. 01.12. Numpy. and Matplotlib
11. 08.12. Machine Learning and ANN: basics and libraries
12. 15.12. Project

Syllabus

  • Introduction: what is programming? Basic concepts
  • Variables, basic types, console input/output, my first program
  • Control flow: if, for, lists, strings and formatting
  • Writing programs: functions and modules, values vs. references
  • Collections (list, tuple, set, dictionary), working with files
  • Exceptions, working with files and directories
  • Object-oriented programming, trees, *recursion
  • Numpy. and Matplotlib
  • Machine Learning and ANN: basics and libraries

Course grading

  • Weekly homework (max. 20 points).
  • Final project (max. 30 points).
  • Bonus assignments.
  • Overall grading: A (50-46), B (45-41), C (40-36), D (35-31), E (30-26), Fx (25-0).