CS101 – Foundations of Business Information Technology
Bachelor of Science in Computing and Business Technologies
Core Course
CS101 – Foundations of Business Information Technology
Course Unit Code: CS101
Type Of Unit: Core
Level of Course Unit: First cycle
Year of Study: First year
Semester: A’ Semester (Fall)
Number of ECTS Credits: 7.5
Class Contact Hours: 36
Face to Face
Face to Face
Prerequisites
None
Course Objectives
The aim of this course is to educate the new generation of computer scientists in terms of existing and new technologies used in the world of information systems and the web. The course will cover fundamental definitions of modern computer science and modern IT systems. The student will get a good understanding of how computer science systems are applied in the real world, and some of the benefits and challenges that businesses face when using those systems.
Learning Outcomes
- Understand some basic definitions around computer science, like algorithms, data structures and databases.
- Understand what kind of IT systems are used in modern organisations, from CRM systems to transaction processing systems.
- Understand how modern IT infrastructures are being built and integrated from databases to networks.
- Understand the role that organizational culture plays in the integration and use of information system.
- Understand the role that new technologies like AI and blockchain can play in the future.
Course Content
Course Features
Planned learning activities and teaching methods
Lectures; in-class discussion and debates; in-class exercises; problem sets; team work; video case studies, team presentations, interactive online learning via Moodle (quizzes, assignments, forums)
Assessment methods and criteria
10% Class participation
40% group assignment
50% exam
Language of Instruction
English
Readings
Recommended or required reading
Textbooks:
1. Paige Baltzan and Amy Phillips. Business Driven Information Systems. McGraw-Hill Education, 5th edition, 2015.
2. ITL Solutions, Introduction to Computer Science, 2011
3. Stylianos Kampakis, The Decision Maker’s Handbook to Data Science, APress, 2020
English (UK) 
Ελληνικά