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Course Information

INFORMATION AND COMMUNICATION TECHNOLOGY
Code Semester Theoretical Practice National Credit ECTS Credit
Hour / Week
AMH117 Fall 3 0 3 3

Prerequisites and co-requisites None
Language of instruction Turkish
Type Required
Level of Course Associate
Lecturer Lect. Volkan Kadir GÜNGÖR
Mode of Delivery Face to Face
Suggested Subject None
Professional practise ( internship ) None
Objectives of the Course To review the fundamental subjects and interests of computer science
Contents of the Course General introduction to computer sciences

Learning Outcomes of Course

# Learning Outcomes
1 Ability to design systems to meet desired needs
2 Ability to implement designs by experiments
3 Ability to create algorithmic solutions to inspect, improve and enhance existing systems by means of analytical approaches
4 Ability to apply basic sciences in the field of computer science

Course Syllabus

# Subjects Teaching Methods and Technics
1 Fundamental Concepts of Computer Sciences Lecture, practice
2 Computer Systems and Peripherals Lecture, practice
3 Introduction to Operating Systems Lecture, practice
4 Operating Systems Lecture, practice
5 Introduction to Algorithms Lecture, practice
6 Flow Charts Lecture, practice
7 Fundamental Concepts of Data Communication Lecture, practice
8 Midterm Exam
9 Microsoft Word Lecture, practice
10 Microsoft Word Lecture, practice
11 Microsoft Excel Lecture, practice
12 Microsoft Excel Lecture, practice
13 Microsoft Excel Lecture, practice
14 Microsoft Power Point Lecture, practice
15 Microsoft Power Point Lecture, practice
16 Final Exam

Course Syllabus

# Material / Resources Information About Resources Reference / Recommended Resources
1 Content is compiled from multiple sources

Method of Assessment

# Weight Work Type Work Title
1 40% Mid-Term Exam Mid-Term Exam
2 60% Final Exam Final Exam

Relationship between Learning Outcomes of Course and Program Outcomes

# Learning Outcomes Program Outcomes Method of Assessment
1 Ability to design systems to meet desired needs 13 1͵2
2 Ability to implement designs by experiments 13 1͵2
3 Ability to create algorithmic solutions to inspect, improve and enhance existing systems by means of analytical approaches 13 1͵2
4 Ability to apply basic sciences in the field of computer science 13 1͵2
PS. The numbers, which are shown in the column Method of Assessment, presents the methods shown in the previous table, titled as Method of Assessment.

Work Load Details

# Type of Work Quantity Time (Hour) Work Load
1 Course Duration 14 3 42
2 Course Duration Except Class (Preliminary Study, Enhancement) 14 3 42
3 Presentation and Seminar Preparation 0 0 0
4 Web Research, Library and Archival Work 0 0 0
5 Document/Information Listing 0 0 0
6 Workshop 0 0 0
7 Preparation for Midterm Exam 0 0 0
8 Midterm Exam 1 2 2
9 Quiz 0 0 0
10 Homework 0 0 0
11 Midterm Project 0 0 0
12 Midterm Exercise 0 0 0
13 Final Project 0 0 0
14 Final Exercise 0 0 0
15 Preparation for Final Exam 1 2 2
16 Final Exam 1 2 2
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