ECTS - Artificial Intelligence Technologies in Business and Management
Artificial Intelligence Technologies in Business and Management (ISL329) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Artificial Intelligence Technologies in Business and Management | ISL329 | Area Elective | 2 | 0 | 0 | 2.5 | 5 |
Pre-requisite Course(s) |
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N/A |
Course Language | Turkish |
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Course Type | Elective Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Demonstration, Discussion. |
Course Lecturer(s) |
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Course Objectives | To enhance understanding, knowledge and skills about applications, opportunities and risks on the Artificial Intelligence technologies and subfields of neural networks, genetic algorithms and machine learning in business management. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Knowledge and skills about applications, opportunities and risks on the Artificial Intelligence technologies and subfields of neural networks, genetic algorithms and machine learning. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Introduction to Network Society and Digital Organizations-1 | Basic concepts about network society and digital organizations should be read. |
2 | Introduction to Network Society and Digital Organizations-2 | A video about digital organizations should be watched. |
3 | New Approaches in Digital Business and Management-1 | Articles on digital business models should be read. |
4 | New Approaches in Digital Business and Management-2 | Readings on digital management strategies should be completed. |
5 | Introduction to Artificial Intelligence Technologies-1 | Articles on the fundamentals of artificial intelligence should be read, and a brief paper should be prepared. |
6 | Artificial Intelligence Technologies and Applications-1 | The application areas of artificial intelligence should be researched, and a brief report should be written. |
7 | Artificial Intelligence Technologies and Applications-2 | Advanced readings on artificial intelligence applications should be conducted. |
8 | Midterm | The topics covered should be reviewed. |
9 | Robotics and Business Management | Articles on robotic technologies should be read. |
10 | Robotics and Business Management Applications | One case study on robotic applications should be conducted. |
11 | Neural Networks in Business Management and Applications | Readings on artificial neural networks should be completed. |
12 | Machine Learning in Business Management and Applications | The basics of machine learning should be researched, and key concepts should be understood. |
13 | Artificial Intelligence, Security, Privacy, Ethic | Recent news on artificial intelligence security and ethics should be investigated. |
14 | Project presentations | Preparation for project presentations should be completed. |
15 | Project presentations | Preparation for project presentations should be finalized. |
16 | Final Exam | The topics covered should be reviewed. |
Sources
Course Book | 1. Nils J. Nilsson, Yapay Zekâ-Geçmişi ve Geleceği, Boğaziçi Üniversitesi Yayınevi, 2018. |
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Evaluation System
Requirements | Number | Percentage of Grade |
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Attendance/Participation | 15 | 16 |
Laboratory | - | - |
Application | 8 | 24 |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | - | - |
Presentation | 1 | 5 |
Project | 1 | 10 |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 1 | 20 |
Final Exam/Final Jury | 1 | 25 |
Toplam | 27 | 100 |
Percentage of Semester Work | 75 |
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Percentage of Final Work | 25 |
Total | 100 |
Course Category
Core Courses | X |
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Major Area Courses | |
Supportive Courses | |
Media and Managment Skills Courses | |
Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
# | Program Qualifications / Competencies | Level of Contribution | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | Have an advanced level of basic theoretical knowledge on the field of public finance in order to obtain the practical gains. | |||||
2 | Identify the issues related to the field of public finance by dealing with it within the framework of the methodological approach, and report and evaluate it from an analytical point of view. | |||||
3 | Understand, interpret and analyse economic and financial events, equipped with knowledge of certain disciplines, especially economics, business and law. | |||||
4 | Develop policies and strategies for solving the problems by establishing the cause-effect relationship related to fiscal and economic issues through theoretical information and the discussions. | |||||
5 | Establish the relationship of public financial management and budget theory with public policies, he/she makes strong budget analysis, develop analysis on public finance and makes a link with the policy implementation | |||||
6 | Understand the tax theory, learning the legal structure, following the legal and financial developments and gaining a professional competence in tax matters effectively develop it. | |||||
7 | Have knowledge of accounting systems in private and public institutions and businesses, analyze and interpret the financial and financial structure of institutions with the knowledge and competence gained. | |||||
8 | Gain knowledge of macroeconomic framework and growth theory, including theoretical and country examples, evaluates economic developments from a theoretical perspective. | |||||
9 | Use foreign language in financial and economic fields, follow international literature, communicate on professional issues. | |||||
10 | Benefit from technological developments in studies specific to its field by using information technologies, digital developments and common software. | |||||
11 | Use qualitative and quantitative methods for the analysis of economic, financial, social and institutional events. | |||||
12 | While fulfilling its academic and professional responsibilities, develop an approach that respects s United Nations sustainable development goals, freedoms, rights of the disadvantaged groups, environment, cultural and moral values. |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
Laboratory | |||
Application | 8 | 1 | 8 |
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 14 | 1 | 14 |
Presentation/Seminar Prepration | 1 | 2 | 2 |
Project | 1 | 8 | 8 |
Report | |||
Homework Assignments | |||
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 1 | 20 | 20 |
Prepration of Final Exams/Final Jury | 1 | 25 | 25 |
Total Workload | 125 |