TEDU 109

Course Code & Number
TEDU 109
Course Title
Digital Competence
Level
BS
Credit Hours/ ECTS Credits
(2+0+2) 3 TEDU Credits, 5 ECTS Credits
Year of Study:
First Year
Semester:
Fall
Type of Course:
Compulsory
Mode of Delivery:
Face-to-face
Language of Instruction:
English
Pre-requisite / Co-requisite::
Pre-requisites: NONE
Co-requisites: NONE
Catalog Description
Fundamentals of computer systems. Basics concepts of Internet, Web, and Networks. Digital Content Creation. Security, Ethics and Privacy. Data Literacy. Communication and Collaboration. Basic concepts of programming. Flow diagram. Variables. Data types. Conditional Statement. Loop. Function. Computational Thinking and Problem Solving. Basic concepts of Artificial Intelligence, Data Science and Machine Learning.
Course Objectives

The general objective of this course is to introduce fundamentals of computer systems and to provide basic concepts of hardware, software, Internet, network, cybersecurity, social media, ethical issues, and privacy. Moreover, this course aims to use computer tools effectively used in learning, study, digital content creation, communication, and collaboration. In addition, fundamentals of programming and how to solve simple problems with computer systems are also in the scope of this course. Another objective of this course is to provide basics of ubiquitous technological topics like; Artificial Intelligence, Data Science and Machine Learning.

Course Learning Outcomes

Upon successful completion of this course, a student will be able to

1.Identify fundamentals of computer and information systems,

2.Use various content creation and collaboration applications and software tools to enhance their personal as well as professional productivity,

3.Recognize ethical, digital security and attack issues,

4.Computational thinking,

5.Illustrate basics of programming constructs like variables and data types,

6.Describe conditional and iteration statements,

7.Write a simple function,

8.Explain basic concepts of artificial intelligence, data science, and machine learning.

Course Coordinator:
Dr. Ayşe Gül Kara Aydemir