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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
-
Keywords

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

  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 Should have sufficient knowledge in mathematics, science, and subjects specific to the relevant engineering discipline.
  2. P02 Should have the ability to use theoretical and applied knowledge in mathematics, science, and related engineering disciplines in complex engineering problems.
  3. P03 Should have the ability to detect, define, formulate, and solve complex engineering problems.
  4. P04 Should have the ability to select and apply appropriate analysis and modeling methods to solve complex engineering problems.
  5. P05 Should have the ability to design a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions.
  6. P06 Should have the ability to apply modern design methods.
  7. P07 Should have the ability to develop, select, and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications.
  8. P08 Should have the ability to use information technologies effectively.
  9. P09 Should have the ability to design experiments, for the study of complex problems or discipline-specific research topics.
  10. P10 Should have the ability to conduct experiments, collect data, analyze and interpret results for the study of complex problems or discipline-specific research topics.
  11. P11 Should have the ability to work in intradisciplinary teams.
  12. P12 Should have the ability to work in interdisciplinary teams.
  13. P13 Should have the skills to work individually.
  14. P14 Should have the ability to communicate effectively verbally and in writing.
  15. P15 Should have the knowledge of at least one foreign language.
  16. P16 Should be able to write effective reports, understand written reports, and prepare design and production reports.
  17. P17 Should have the ability to make effective presentations.
  18. P18 Should have the ability to give and have clear and understandable instructions.
  19. P19 Should gain consciousness (awareness) about the necessity of lifelong learning.
  20. P20 Should have the ability to access information.
  21. P21 Should have the ability to follow developments in science and technology and constantly renew himself/herself.
  22. P22 Should gain the awareness of professional and ethical responsibility and should act in accordance with ethical principles.
  23. P23 Should gain knowledge about the standards used in engineering applications.
  24. P24 Should gain knowledge about project management, risk management, and change management practices in business life.
  25. P25 Should gain awareness about entrepreneurship, and innovation.
  26. P26 Should gain knowledge about development in sustainability.
  27. P27 Should gain knowledge about the effects of engineering practices on health, environment, and security at universal and social dimensions and the problems of the age reflected in the field of engineering.
  28. P28 Awareness should be gained about the legal consequences of engineering solutions.

Po-Lo Matrix

LO P01 P02 P03 P04 P05 P06 P07 P08 P09 P10 P11 P12 P13 P14 P15 P16 P17 P18 P19 P20 P21 P22 P23 P24 P25 P26 P27 P28 Average
L01 - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
L02 - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
L03 - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
L04 - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
L05 - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
L06 - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
L07 - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
L08 - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
L09 - - - - - - - - - - - - - - - - - - - - - - - - - - - - -