ARTIFICIAL INTELLIGENCE AWARENESS

Course Description

This course provides an accessible and engaging introduction to Artificial Intelligence (AI), focusing on its core concepts, real-world applications, and broader impact on society. Students from all academic backgrounds will explore how AI shapes everyday life, with special attention to its role in education, language learning (such as platforms like Duolingo), and classroom assignments. The course highlights how AI agents are increasingly used in areas like tutoring, content generation, and personalized learning support. Through real-world examples and discussions, students will learn about the potential and limitations of AI, while also understanding key ethical issues such as fairness, privacy, and responsible use.

ARTIFICIAL INTELLIGENCE AWARENESS

Evaluation Tools (Active Term)

Course outcomes

No course outcomes have been defined yet.

Course Syllabus

Reference Books & Course Materials

1. 01 Philip C. Jackson, Introduction to Artificial Intelligence, Third Edition, Dover Publications, 2019.

Learning Outcomes

1. L01 Define fundamental AI concepts, distinguish ANI from AGI, and explain why AI is transforming industries. SOLO 3.3
2. L02 Describe core AI capabilities and limitations, and identify tasks suitable for AI automation. SOLO 2.5
3. L03 Explain how AI projects are structured and recognize AI’s role in business and organizational transformation. SOLO 3.3
4. L04 Analyze how organizations adopt AI, identify roles in AI transformation, and evaluate its potential to augment or automate tasks across professions. SOLO 3.7
5. L05 Explain generative AI concepts, differentiate between prompting, fine-tuning, and RAG, and illustrate common applications (text, image, audio). SOLO 3.7
6. L06 Recognize AI’s limitations, sources of bias, and risks from adversarial manipulation, and discuss fairness, transparency, privacy, and responsible AI guidelines. SOLO 3.5
7. L07 Assess AI’s impact on jobs, workforce transitions, and future skill requirements, and analyze its effects across sectors such as education, healthcare, and governance. SOLO 4.5
8. L08 Explain different approaches to AI regulation, evaluate policy frameworks, and critically reflect on possible AI futures and their ethical and social implications. SOLO 4.75
9. L09 Explaing and Asses AI Philosophy SOLO 4.5

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