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Modern Information Technology

Course Title: Modern Information Technology
Description	This course provides a comprehensive overview of Modern Information Technology and its role in society. Topics include the fundamentals of computer hardware and software, networking and the internet (LAN, WAN, 5G, IoT), cloud computing and virtualization, data management with SQL/NoSQL, and cybersecurity practices. Students will also explore artificial intelligence, blockchain, and quantum computing, along with modern applications such as e-governance, e-commerce, e-learning, and healthcare IT. The course concludes with future trends and ethical considerations, including green IT, privacy, and the digital divide.
Semester	Autumn 2025
Neptun code	GEIAL551-Ma
Instructor	Dr. Nasraldeen Khleel
Credit Hours	5
Attendance Requirement	Students are required to attend at least 60% of the scheduled classes to be eligible for the course signature
Examination	The examination is written, and students will receive some theoretical questions and some practical tasks from the studied material

Topics and Schedule

Lecture #	Topic
Lecture 1	Introduction to Information Technology (IT) – history and role in society
Lecture 2	Computer Hardware and Software – basics of systems, Operating System (OS), applications
Lecture 3	Networking and Internet – Local Area Network (LAN), Wide Area Network (WAN), protocols, 5G, Internet of Things (IoT)
Lecture 4	Cloud Computing and Virtualization – services, benefits
Lecture 5	Data and Databases – Big data and analytics
Lecture 6	Data and Databases – Structured Query Language (SQL) /NoSQL basics
Lecture 7	Data Visualization for Engineering: Real-time data visualization and customization for reports
Lecture 8	Data Analysis and Manipulation: Introduction to pandas for tabular data. Cleaning and processing experimental or simulation data
Lecture 9	Data Analysis and Manipulation: Descriptive statistics and basic data analysis
Lecture 10	Solving Engineering Problems with Python: Case studies: heat transfer, structural analysis, fluid mechanics, etc. Solving differential equations with SciPy. Engineering optimization problems
Lecture 11	Introduction to SymPy for symbolic mathematics: Simulating simple engineering systems (e.g., pendulum, electrical circuits). Introduction to OpenCV or similar tools for basic image analysis in engineering
Lecture 12	Excel Visual Basic for Applications (VBA) programming