Artificial Intelligence Algorithms Field of study: Computer Science
Programme code: 08-S2INIA15.2016

Module name: Artificial Intelligence Algorithms
Module code: 08-IN-ISI-S2-ASI
Programme code: 08-S2INIA15.2016
Semester: winter semester 2017/2018
Language of instruction: English
Form of verification: exam
ECTS credits: 3
Description:
The aim of classes in this module is making student familiar with chosen techniques and methods of artificial intelligence, with special emphasis on classification methods. Another important aspect undertaken during the module is concluding making use of diffused logics, when input concepts are not directly and unambiguously defined. Moreover, the student gets knowledge and skills from the field of neural networks, which can be used to solve complex optimization tasks or to context recognition.
Prerequisites:
(no information given)
Key reading:
(no information given)
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
Can design IT systems supported by artificial intelligence algorithms. [ASI -U_5]
 K_2_A_I_U08 [2/5] K_2_A_I_U17 [1/5] K_2_A_I_U18 [2/5]
Is able to calculate the degree of membership in a diffused series and to correctly identify certain type of membership function taking advantage of mathematical notation [ASI -U_6]
 K_2_A_I_U08 [1/5] K_2_A_I_U18 [2/5]
Can use naïve Bayes classifier and k?nearest neighbors algorithm for defined problems at given limitations. [ASI -U_7]
 K_2_A_I_U08 [1/5] K_2_A_I_U17 [2/5] K_2_A_I_U18 [1/5]
Possesses basic knowledge from the field of artificial intelligence algorithms [ASI -W_1]
 K_2_A_I_W08 [5/5]
Has basic knowledge from the field of diffused logics, knows basic logic operations in reference to diffused series and differentiates basic types of membership functions. [ASI -W_2]
 K_2_A_I_W08 [3/5]
Possesses basic knowledge from the field of machine learning (chosen methods of controlled and uncontrolled learning) [ASI -W_3]
 K_2_A_I_W08 [2/5] K_2_A_I_W18 [2/5]
Possesses basic knowledge from the field of genetic algorithms [ASI -W_4]
 K_2_A_I_W08 [1/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Exam [ASI _w_1]
The goal is to verify theoretical knowledge gained during lectures and practical skills gained during laboratory classes. The exam in the form of test includes variety of closed multiple?choice question and practical tasks.
 ASI -W_1 ASI -W_2 ASI -W_3 ASI -W_4
Control tests [ASI _w_2]
Tests after presentation of subsequent techniques or group of issues concerning artificial intelligence.
 ASI -U_5 ASI -U_6 ASI -U_7
Group reports [ASI _w_3]
Use of the acknowledged artificial intelligence methods to classification tasks or in the process of concluding, taking advantage of data acquired from repository: Machine Learning Repository, or artificially generated by the student.
 ASI -U_5 ASI -U_6 ASI -U_7 ASI -W_1 ASI -W_2 ASI -W_3 ASI -W_4
Form of teaching Student's own work Assessment of the learning outcomes
Type Description (including teaching methods) Number of hours Description Number of hours
lecture [ASI _fs_1]
Providing content of education in verbal form, using content visualization. Concentrating on conceptually difficult issues.
 15
Familiarizing with subject of the lecture.
 15 Exam [ASI _w_1]
laboratory classes [ASI _fs_2]
Detailed preparation to solve problems stressing methodology of proceedings, pointing sequence of proceedings. Solving tasks of content. Quizzes and multiple choice tests together with group discussion over possible answers.
 30
Solving tasks from subsequent topics together with analyses of the existing solutions (available on the teacher’s websites). Applying knowledge concerning artificial intelligence, gained during lectures and laboratory classes, on the basis of data generated by students, which allows its ordering.
 30 Control tests [ASI _w_2] Group reports [ASI _w_3]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)