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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 PO1: Engaged in insightful thinking leading to self-learning and lifelong learning.
  2. P02 PO2: Established a general knowledge of economics sufficient to work independently through specific learned techniques generated via individual efforts and study.
  3. P03 PO3: Reached the required knowledge and skills to understand social, economic and legal issues both within national, international and global contexts and apply theoretical knowledge of economics to practice.
  4. P04 PO4: Adopted the ability to critically evaluate, analyze and interpret information gathered through the use of related statistical software programs to suggest creative solutions for economic problems and make relevant economic decisions.
  5. P05 PO5: Been aware of gathering and analyzing data through the application of appropriate technological tools in an ethical and safe manner in order to generate economic decisions and policy suggestions.
  6. P06 PO6: Been equipped with conceptual and analytical skills essential for team-working and collaborations for economic decision making for a variety of economic concepts in national and global environment.
  7. P07 PO7: Endowed with both oral and written communication skills within the economic field to effectively study and work in an international environment
  8. P08 PO8: Been able to transfer theoretical knowledge to real life economic environment: to generate policies for microeconomic and macroeconomic problems faced by individuals, firms and governments at national, international and global context.
  9. P09 PO9: Developed an ability to apply economic analysis to everyday problems in real world through the development of ethical perspectives and social responsibilities at work and in personal life.

Po-Lo Matrix

LO P01 P02 P03 P04 P05 P06 P07 P08 P09 Average
L01 - - - - - - - - - -
L02 - - - - - - - - - -
L03 - - - - - - - - - -
L04 - - - - - - - - - -
L05 - - - - - - - - - -
L06 - - - - - - - - - -
L07 - - - - - - - - - -
L08 - - - - - - - - - -
L09 - - - - - - - - - -