ARTIFICIAL INTELLIGENCE AWARENESS
- Course
- APSC123 - ARTIFICIAL INTELLIGENCE AWARENESS
- Department
- Management Information Systems - English - Undergraduate
- Course Type
- Online Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 6
- T+P+L
- 0 + 0 + 3
- Course Coordinator(s)
- Asst. Prof. Dr. Kian JAZAYERI
- Prerequisite
- -
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)
| Item | Type | Weight (%) |
|---|---|---|
| Final Exam | Final | 40 |
| Midterm Exam | Midterm | 30 |
| Homework 1 | Assignment | 15 |
| Homework 2 | Assignment | 15 |
| Total | 100 | |
Course outcomes
No course outcomes have been defined yet.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | What is AI? (ANI vs AGI, Machine Learning, Data, Why Now?) |
| Week 2 | How AI Works in Practice (Machine Learning basics, examples, what AI can/can’t do) |
| Week 3 | Building AI Projects (workflow, selecting use cases, data importance) |
| Week 4 | Building AI in Organizations (AI strategy, roles in AI teams, pilot projects) |
| Week 5 | Generative AI Introduction (LLMs, image/audio/video generation, prompting) |
| Week 6 | Generative AI in Practice (software applications, RAG, fine-tuning, cost of AI) |
| Week 7 | Generative AI and Business (automation vs. augmentation, job task analysis) |
| Week 8 | Midterm Examination |
| Week 9 | AI and Society (AI hype, limitations, bias, adversarial attacks) |
| Week 10 | AI Ethics and Responsible AI |
| Week 11 | AI and Future of Work (jobs at risk, new opportunities, skills needed), The Future of AI (speculative futures, opportunities, risks, AGI debates) |
| Week 12 | AI in Daily Life (healthcare, education, governance, developing economies) |
| Week 13 | Policy and Regulation (global perspectives, EU AI Act, governance frameworks) |
| Week 14 | Philosophy of Artificial Intelligence |
| Week 15 | Final Exam |
Reference Books & Course Materials
- 01 Philip C. Jackson, Introduction to Artificial Intelligence, Third Edition, Dover Publications, 2019.
Learning Outcomes
- L01 Define fundamental AI concepts, distinguish ANI from AGI, and explain why AI is transforming industries. SOLO 3.3
- L02 Describe core AI capabilities and limitations, and identify tasks suitable for AI automation. SOLO 2.5
- L03 Explain how AI projects are structured and recognize AI’s role in business and organizational transformation. SOLO 3.3
- 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
- L05 Explain generative AI concepts, differentiate between prompting, fine-tuning, and RAG, and illustrate common applications (text, image, audio). SOLO 3.7
- 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
- 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
- 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
- L09 Explaing and Asses AI Philosophy SOLO 4.5
Program Outcomes
- P01 Demonstrate an understanding of the core subfields of psychology — including but not limited to clinical, developmental, cognitive, social, and biological/neuroscientific psychology — and their interconnections with other scientific disciplines, critically evaluating the value of a multidisciplinary approach to scientific inquiry in psychology.
- P02 Apply scientific methods, research techniques, measurement and psychometric principles (e.g., reliability, validity, scale development/adaptation), and quantitative/statistical reasoning to investigate psychological phenomena, recognizing methodological strengths, limitations, common reasoning fallacies, and the flaws of pseudoscience.
- P03 Employ logical, intuitive, and creative thinking to analyze psychological concepts, evaluate theories (including their historical and philosophical development), synthesize information, and solve complex problems related to cognition and behavior.
- P04 Integrate psychological theories and findings into practical settings (e.g., business, policy, clinical/counseling contexts, and daily life), applying foundational applied skills such as interviewing, observation, and case formulation, drawing meaningful conclusions to inform individual, organizational, and societal practices.
- P05 Describe key ethical principles in psychological research and practice, critically applying these principles to dilemmas across academic, professional, and everyday contexts.
- P06 Recognize how individual differences (e.g., beliefs, values, backgrounds) impact behavior and relationships; use psychological knowledge to prevent or resolve intercultural and interpersonal conflicts and promote inclusive, respectful interactions.
- P07 Exhibit self-regulation and self-awareness, demonstrating a commitment to psychological well-being, effective time management, constructive incorporation of feedback, and ongoing personal and professional development.
- P08 Collaborate effectively in diverse teams, demonstrating responsibility, bias awareness, conflict resolution skills, and leadership in achieving collective goals.
- P09 Communicate psychological knowledge clearly and appropriately for academic, professional, and public audiences using inclusive language, both in written and oral formats, and by accurately summarizing and presenting research findings.
- P10 Use information and communication technologies (including AI and digital media) responsibly and effectively for research, collaboration, and the dissemination of psychological knowledge.
- P11 Embrace lifelong learning and adaptability in response to evolving psychological knowledge and societal needs, engaging with global perspectives and demonstrating intercultural awareness.
Po-Lo Matrix
| LO | P01 | P02 | P03 | P04 | P05 | P06 | P07 | P08 | P09 | P10 | P11 | Average |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| L01 | - | - | - | - | - | - | - | - | - | - | - | - |
| L02 | - | - | - | - | - | - | - | - | - | - | - | - |
| L03 | - | - | - | - | - | - | - | - | - | - | - | - |
| L04 | - | - | - | - | - | - | - | - | - | - | - | - |
| L05 | - | - | - | - | - | - | - | - | - | - | - | - |
| L06 | - | - | - | - | - | - | - | - | - | - | - | - |
| L07 | - | - | - | - | - | - | - | - | - | - | - | - |
| L08 | - | - | - | - | - | - | - | - | - | - | - | - |
| L09 | - | - | - | - | - | - | - | - | - | - | - | - |