Teaching

1905220: Ethics of Artificial Intelligence and Data Science

Semester: Spring

Offered: 2024/2025

This course explores the ethical dimensions and societal impacts of AI and data science technologies. Students will examine critical issues including algorithmic bias, privacy concerns, transparency in machine learning, accountability in automated decision-making, and the broader social implications of intelligent systems. The curriculum balances theoretical frameworks with practical case studies, encouraging students to develop nuanced perspectives on responsible innovation.

Topics covered include:

• Ethical frameworks and ethical theories for evaluating AI systems

• Fairness, accountability, and transparency in algorithms

• Data privacy and informed consent

• Responsibility, Accountability, automation, and autonomous agents

• Bubble filters, AI Plagiarism, Responsible research and development practices

• Philosophical inquiries into consciousness and machine sentience

• Ethical considerations around AGI (Artificial General Intelligence) and ASI (Artificial Superintelligence)

• Critical analysis of singularity theories and their societal implications

The course encourages deep philosophical discussions about what constitutes consciousness, the possibility and implications of machine sentience, and how we might approach the development of increasingly autonomous systems. We explore various perspectives on the path toward AGI and potential superintelligence, examining both utopian and dystopian visions of technological singularity.

Many of the course materials are available on my YouTube channel, reflecting my commitment to "tech with a human heart" and making quality education accessible to everyone, whether they're enrolled JU students or independent learners.

1902351: Multimedia

Semester: Spring

Offered: 2024/2025

This course is mainly designed to introduce the theoretical and mathematical concepts of digital media including images, audio, animation and video. The difference between “analog” and “digital” media is discussed. Different types of digital media are outlined and their digital storage process is explained in detail. The digital media encoding and decoding concepts are also explained. In addition, different types of digital media compression techniques are introduced. The most popular file formats are outlined for each media type.  Finally, the Multimedia related hardware, software, quality and web-related issues are also discussed.  

1900103 : Modern Digital skills

Semester: Spring

Offered: 2024/ 2025

This course aims to enhance the students’ digital knowledge and skills, placing a spotlight on Artificial Intelligence (AI) and cutting-edge digital technologies, to equip them for current and future jobs. The course allows participants to learn the foundations of the digital world and enable them to better utilize technology to advance their careers. The course material includes, but is not limited to: types of data, information, and content; digital identity; digital content creation in all forms; cyber-security and safety; collaborating and working online; global trends and technologies such as Big Data, Cloud Computing, Artificial Intelligence, Internet of Things, Gamification; Balanced use of technology and social media; and digital career competencies needed in the current job market. Aligned with Education for Sustainable Development (ESD) and Sustainable Development Goals (SDGs), it instills responsibility for inclusive and sustainable practices in the digital era. As the digital landscape evolves, the course content is continuously updated to keep students well-prepared and informed about emerging digital technologies shaping the future. The course employs experiential and active learning methods, including interactive lectures, collaborative activities, and the use of digital tools. Assessment methods include exams, assignments, practical tasks and the integration of professional certifications, providing students with hands-on experience and industry-recognized credentials that enhance their career prospects.  

1905320: Artificial Intelligence 

Semester: Fall

Offered: 2024/ 2025

This course aims to give an Introduction to artificial intelligence (concepts, research areas and applications), Propositional logic, First order logic, Representing simple domains in First order logic, Resolution refutation proofs; Logic programming (Prolog), Exhaustive search methods; Heuristic search methods; Production systems; Architecture of expert systems, and Introduction to Machine Learning. 

1902203: Computer Skills and Documenatation

Semester: Spring

Offered: 2023/2024

The course introduces the students to the documentation and computing ethics. Topics include: different types of technical reports and documents such as books, articles, proposals, user manuals, project reports, memorandums, etc. in ethical and professional ways; ethical writing pertaining referencing, citation, quotation, and plagiarism; computing ethics such as computers and information systems in workplaces, crimes, computer abuse and misuse, cyber bullying and stalking, privacy, confidentiality, anonymity, intellectual property, professional responsibility, and globalization (law, cyber-business, e-transactions); various code of ethics and guidelines to computing professionals and users, it also includes ethics in social media and freedom of expression 

1915101: Linear Algebra for Computational Science

Semester: Spring

Offered: 2023/ 2024

This course provides an introduction to essential linear algebra concepts with a focus on applications in data science and artificial intelligence. Topics include systems of linear equations, matrix calculus, vectors, and basic vector operations. Emphasizing problem-solving skills, the course enables students to analyze mathematical arguments effectively. Practical application is emphasized through solving computational problems in data science using the Python programming language. 

1942102: Computer skills for Humanities

Semester: Summer

Offered: 2023/2024

This introductory course is designed to lay down a solid foundation in the area of information technology. The course develops critical thinking and problem solving skills. Moreover, it aims to teach students how to use common software for organizing, searching and computing with emphasis on "real world" business-related tasks. Students will have the opportunity to practice and implement applications in the lab. This course has four modules: - Problem solving including problem analysis, algorithms, flowcharts and pseudo codes. - Spreadsheets (MS Excel) including functions, charts, filtering, sorting, macros and scenarios. - Presentations including creating slides, tables, charts, animation effects, page transitions. Printing and displaying slides. - Introduction to Information systems and applications including computer applications in everyday activities, Health care, communication and emergency support, e-commerce. 

1902103: Computer skills for Medical students

Semester: Fall

Offered: 2023/2024

This course empowers the medical students with the necessary computer skills associated with the health information systems. It also provides entry level knowledge for conducting medical research experiments and utilizing the available software tools including spread sheet (Excel) and database (Access). Moreover, it introduces the necessary computer skills for understanding medical experimental settings, hypotheses testing, and statistical tests such as: student Ttest as well as the computer skills for computing both the correlation and regression. Furthermore, this course includes case studies for both a database in health information system and medical data analysis 

Advanced Topics in Modern Digitall Skills, Problem Soving and coding with Python

Semester: Summer

Offered: 2024/2025

This course, "Problem Solving and Coding," is designed specifically for students who aim to develop essential programming and problem-solving skills without prior experience in coding. Python, known for its simplicity and versatility, is widely used in scientific research, data analysis, and healthcare applications.

The course covers foundational programming concepts such as variables, data types, decision-making, loops, functions, and data structures. Students will also explore techniques for solving problems using Python, with examples tailored to scientific and medical contexts, including data processing, analysis, and visualization.

By the end of the course, students will be able to apply Python programming to automate tasks, process experimental or clinical data, and support their studies and research activities.