COURSE UNIT TITLE

: ARTIFICIAL INTELLIGENCE FOR TRADE AND BUSINESS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IBS 4498 ARTIFICIAL INTELLIGENCE FOR TRADE AND BUSINESS ELECTIVE 3 0 0 5

Offered By

International Trade and Business (English)

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR BERNA KIRKULAK ULUDAĞ

Offered to

International Trade and Business (English)

Course Objective

The objective of this course is to provide students with a foundational understanding of how Artificial Intelligence (AI) is transforming trade and business. Students will explore AI applications in various business domains, including market analysis, supply chain management, customer relationship management, and decision-making. The course will also address ethical considerations, regulatory aspects, and future trends in AI for trade and business.

Learning Outcomes of the Course Unit

1   Students will be able to demonstrate fundamental knowledge of AI concepts, machine learning, and data-driven decision-making in business environments.
2   Students will be able to analyze the role of AI in international trade, including its impact on logistics, market intelligence, and trade finance.
3   Students will be able to evaluate AI-driven business strategies and their implications for competitive advantage in global markets.
4   Students will be able to develop an AI-enhanced business model and present it in both written and oral formats.
5   Students will gain experience in working with AI-based case studies and applying AI tools to real-world trade and business scenarios.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction: Overview of AI in trade and business
2 Fundamentals of AI: Introduction to AI, machine learning, and deep learning
3 AI in Business Strategy: Leveraging AI for business decision-making and competitive advantage
4 AI in International Trade: Applications in logistics, supply chain, and trade finance
5 Implementation Week : AI tools for business and trade
6 AI Driven Market Analysis: Predictive analytics, customer segmentation, and trend forecasting
7 AI in Customer Experience: Chatbots, recommendation engines, and personalization
8 Ethical and Regulatory Considerations: AI governance, bias, and legal implications in business
9 Guest Speaker Week: Industry expert insights on AI applications in trade
10 AI for Digital Marketing and E-commerce: Personalized marketing, ad targeting, and automation
11 AI in Financial Decision-Making: Credit scoring, risk assessment, and fraud detection
12 General Review: Course summary and QA session
13 Term Project Presentations
14 Term Project Presentations

Recomended or Required Reading

Meltzer, J. P. (2018). The impact of artificial intelligence on international trade. Center for
technology Innovation at Brookings, 9.
Gupta, P., & Singh, N. (2024). Artificial Intelligence Tools for Reshaping E-Business and Trade.
In Handbook of Artificial Intelligence Applications for Industrial Sustainability (pp. 249-273). CRC
Press.
Agrawal, A., Gans, J., Goldfarb, A. (2017). How AI will change the way we make
decisions. Harvard Business Review, 26(July), 1-7.

Planned Learning Activities and Teaching Methods

1- Lecture
2- Presentations
3- Term Projects
4- Assignments

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MT Midterm
2 ASS Assignment
3 TP TermProject
4 BNS BNS MT * 0.30 + ASS * 0.30 + TP * 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

1. The learner will explain AI fundamentals, interpret its applications in business, and discuss ethical
considerations.
2. The learner will analyze and interpret AI-driven business strategies and assess their impact on trade and
commerce.
3. The learner will solve case studies involving AI in trade and business and contribute to class discussions.
4. The learner will develop and present AI-enhanced business models in group projects.
5. The learner will apply AI tools and research methods effectively in their assignments and presentations.

Language of Instruction

English

Course Policies and Rules

1. Attending at least 70 percent of lectures is mandatory.
2. Plagiarism of any type will result in disciplinary action.
3. Students should attend the classes on time.

Contact Details for the Lecturer(s)

Prof.Dr. Gülüzar Kurt Gümüş
E-mail: guluzar.kurt@deu.edu.tr

Office Hours

By appointment.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 7 3 21
Student Presentations 7 3 21
Preparations before/after weekly lectures 12 2 24
Preparation for midterm exam 1 15 15
Project Preparation 1 12 12
Preparing assignments 3 6 18
Preparing presentations 1 15 15
Midterm 1 1,5 2
TOTAL WORKLOAD (hours) 128

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.1222143
LO.2323434
LO.3233535
LO.42244455
LO.522345535

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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