FUNDAMENTALS OF COMPUTING

Course Description

This course serves as an introduction to the basic component of information systems, hardware, software, data, people and networks. Topics covered includes computer networks and communications, systems and application software, computer hardware and its operation, the internet and the world wide web, algorithms, pseudocodes and flowchart. After the completion of the course, students will be able to differentiate between various operating systems and application programs. They will be able to identify computer tools that can be used to assist with various common computer applications. They will also gain the fundamental understanding of the history and operation of computers, programming, and web design.

FUNDAMENTALS OF COMPUTING

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

1. 01 Identify the fundementals and working principles of the software and the harware of computer systems
2. 02 Evaluate and express computer numbering formats
3. 03 Identify funademental concepts of computer architecture
4. 04 Recognise basics of operating systems and computer networks
5. 05 Examine problems and their solutions using computer algorithms: pseudocode and flowchart

Course Syllabus

Reference Books & Course Materials

1. 01 J. Glenn Brookshear, Computer Science: An overview, Pearson Addison Wesley, 2008.
2. 02 Maureen Sprankle, Problem Solving and Programming Concepts, Pearson Prentice Hall, 2006.
3. 03 June Jamrich Parson, Dan Jao; Computer Concepts Introductory, Cengage Learning, 2013.

Learning Outcomes

No learning outcomes have been defined.

Program Outcomes

1. P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
2. P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
3. P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
4. P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
5. P05 Utilize modern computing techniques to handle real-world problems characterized by massive amounts of data, such as parallel and distributed computing and machine learning.
6. P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
7. P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
8. P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
9. P09 Be able to effectively integrate data‐based solutions into the user environment and help non-technical professionals in exploring, visualizing, and using these solutions
10. P10 Understand their obligations under professional and ethical standards in relation to matters like data ownership and citation, data security and sensitivity and the privacy implications of data analysis.

Po-Lo Matrix

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