Vocatıonal School
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Course Information

COMPUTER
Code Semester Theoretical Practice National Credit ECTS Credit
Hour / Week
BTP101 Fall 3 0 3 4

Prerequisites and co-requisites
Language of instruction Turkish
Type Required
Level of Course Associate
Lecturer Assistant professor Dr. Ziya Gökalp Altun
Mode of Delivery Face to Face
Suggested Subject
Professional practise ( internship ) None
Objectives of the Course To review the fundamental subjects and interests of computer engineering
Contents of the Course General introduction to computer sciences

Learning Outcomes of Course

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

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 apply basic sciences in the field of computer sciences 10͵16 1͵2
2 Ability to design systems to meet desired needs 10͵16 1͵2
3 Ability to implement designs by experiments 10͵16 1͵2
4 Ability to create algorithmic solutions to inspect, improve and enhance existing systems by means of analytical approaches 10͵16 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 1 1
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 4 4
16 Final Exam 1 1 1
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