INDUSTRIAL ENGINEERING
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
GEP0021 Artificial Intelligence and Its Application Areas Fall 3 0 3 5
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: GE-Elective
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Hybrid
Course Coordinator : Assist. Prof. BURCU ALARSLAN ULUDAŞ
Course Objectives: The objective of this course is to provide the student with a perspective on artificial intelligence terminology, common methods, artificial intelligence applications in the real world and their effects and mis-uses. During the course, the student will learn the most used artificial intelligence algorithms and their applications in case studies, and will brainstorm on weekly discussion topics.

Learning Outcomes

The students who have succeeded in this course;
1) The student will be able to understand what artificial intelligence can and cannot do.
2) The student will be able to explore the applications of artificial intelligence in different fields.
3) Student will be able to apply artificial intelligence solutions to real world problems.
4) The student will be able to discuss artificial intelligence in terms of bias and fairness.
5) The student will be able to understand the effects of artificial intelligence in the real world.

Course Content

In this course, students will learn what artificial intelligence technology is, how it works, and its capabilities. In this course, in which different application areas are discussed comprehensively, students will have the opportunity to evaluate the benefits and difficulties of the application areas through discussion topics. Students will gain a perspective in identifying needs in order to solve real-world problems with artificial intelligence approaches, and will also be involved in discussions about international artificial intelligence ethical principles such as objectivity, transparency, explainability, and accountability. They will have a high awareness to evaluate the processes of application of artificial intelligence in different business areas from start to finish, in general, from technical and social aspects.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) "What is AI? Where do we use AI? Phylosophy of AI; AI in problem solving; Case Study - Chicken Crossing Puzzle Case Study - Towers of Hanoi; Case Study - Tic Tac Toe"""
2) "AI in Healthcare Predicting health risk; Smart identification and diagnosis; Smart prescription; Smart imaging & segmentation; Personalized healhcare; AI in psychology; Discussion: Chest Xray Classification / Segmentation"
3) "AI in Entertainment and Gaming Content personalization; Metadata tagging; User engagement; Promotion and advertising Captioning / Subtitle generation; Discussion: In-app purchases"
4) "AI in Social Media How to organize massive data; Setting trends; Hashtags; Discussion: Using AI to manipulate user choices; Discussion: Using AI for disaster response"
5) "AI in Security Cyber attacks; Data security; Anti fraud systems; Biometric recognition / verification Know Your Customer (KYC)"
6) "AI in Finance Insuring, banking, asset management; Cryptocurrency & Crypto banks Algorithmic trading; Financial risk management; Anti-Money Laundering (AML)"
7) "AI in Travel & Transportation Automated travel services; Traveler behaviors; Personalized travel experience; Logictics route optimization; Warehouse operations"
8) "AI in Robotics Robotics applications; Robotic packaging; Open source robotics; Robotics in healthcare, agriculture, automative, supply chain, military; Discussion: Robot ethics"
9) "AI in E-commerce Transforming the shopping experience; Virtual assistants; Addressing consumer needs through deeper insights; Provide personalized or targeted offers; Consumer behavior forecasting; Inventory management; Smart customer service"
10) "AI in Manifacturing and Business Optimization of supply chain; Optimization of staff, inventory control, energy consumption Optimization of raw material supply; Predictive and prescriptive data analysis; Factory automation; Discussion: What AI can / cannot do"
11) "AI in Law E-discovery; Expertise automation; Legal search and document management; Contract and litigation document analytics and generation; Predictive analysis"
12) "Human Centered AI & Ethics AI in non-profit sectors; AI for social good; AI in education; AI in sociology; AI bias and fairness; Misuses of AI; Machine morality - Artificial Moral Agents (AMA); Transparency & Explainability; Discussion: Automation results in unemployment or new opportunities?"
13) "Adverse uses of AI Adversarial attacks on AI; Possible future adjustments; Discussion"
14) "Thinking about AI AI and developing economies ; AI Ethics ; AI and jobs ; Social Impacts of AI ; Political Impacts of AI "

Sources

Course Notes / Textbooks: Artificial Intelligence: A Modern Approach
References: "50 Soruda Yapay Zeka, Cem Say
SuperIntelligence, Nils Nilsson
Yapay Zeka Geçmişi Geleceği, Nils Nilsson
The Rise of the Robots, Martin Ford
Privacy, Eirik Lokke
Life 3.0 — Being Human in the Age of Artificial Intelligence, Max Tegmark"

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Quizzes 4 % 40
Midterms 1 % 20
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 60
PERCENTAGE OF FINAL WORK % 40
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Study Hours Out of Class 14 3 42
Quizzes 4 8 32
Midterms 1 4 4
Final 1 4 4
Total Workload 124

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Build up a body of knowledge in mathematics, science and industrial engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems.
2) Identify, formulate, and solve complex engineering problems; select and apply proper analysis and modeling methods for this purpose.
3) Design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose. The ability to apply modern design methods to meet this objective.
4) Devise, select, and use modern techniques and tools needed for solving complex problems in industrial engineering practice; employ information technologies effectively.
5) Design and conduct experiments, collect data, analyze and interpret results for investigating the complex problems specific to industrial engineering.
6) Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working independently.
7) Demonstrate effective communication skills in both oral and written English and Turkish. Writing and understanding reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instructions.
8) Recognize the need for lifelong learning; show ability to access information, to follow developments in science and technology, and to continuously educate him/herself. 4
9) Develop an awareness of professional and ethical responsibility, and behaving accordingly. Information about the standards used in engineering applications. 3
10) Know business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development. 4
11) Know contemporary issues and the global and societal effects of modern age engineering practices on health, environment, and safety; recognize the legal consequences of engineering solutions. 4
12) Develop effective and efficient managerial skills.