School of Economics and Administrative Sciences \ Business Administration
Course Credit
ECTS Credit
Course Type
Instructional Language
Programs that can take the course
Business Administration Bachelor's Degree Program
This course provides a comprehensive overview of how artificial intelligence (AI) and data analytics are applied in business contexts. Students will gain essential analytical skills to support data-driven decision-making processes. The course covers basic SQL querying, data management, and visualization techniques, along with hands-on practice using tools such as Excel, Tableau, and Power BI. Additionally, key concepts in machine learning, artificial intelligence, and data science will be explored with a focus on their practical applications in areas such as marketing, operations, and strategic management. The course will also include an introduction to how AI and data analytics can be integrated into Enterprise Resource Planning (ERP) systems. By the end of the course, students will be equipped to generate insights from data using analytical tools and contribute effectively to strategic decision-making processes within businesses.
Textbook and / or References
1. Provost, F., & Fawcett, T. (2013). Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. O’Reilly Media.
2. Tanimura, C. (2017). SQL for Data Analysis: Advanced Techniques for Transforming Data into Insights. O'Reilly Media.
3. Knaflic, C. N. (2015). Storytelling with Data: A Data Visualization Guide for Business Professionals. Wiley.
4. MS Excel.
The aim of this course is to introduce students to the concepts of artificial intelligence and data analytics in businesses, provide them with basic data management and SQL skills, teach them how to use data visualization tools, and provide them with an understanding of the applications of artificial intelligence in the business world. It also aims to develop students' analytical thinking skills so that they can make data-driven decisions and use technical English terms.
1. Define the concepts of artificial intelligence and data analytics and explain the impact of these technologies on strategic decision-making processes in businesses.
2. Demonstrate the ability to extract, filter and analyze data from databases by writing basic SQL queries.
3. Be able to visualize data with tools such as Excel, Tableau and Power BI and create KPIs appropriate for the business context.
4. Understand the basic functions of machine learning and artificial intelligence applications and evaluate them in areas such as marketing, operations and customer analytics.
5. Integrate data analytics processes into business strategies and offer data-driven solution suggestions in different business scenarios.
6. Understand the concepts of artificial intelligence and data analytics in English and can use English in this field.
Week 1: Introduction to Artificial Intelligence and Data Analytics in Business
Week 2: Data-Driven Decision Making and Business Applications
Week 3: Fundamentals of Data Management and Data Types
Week 4: Introduction to SQL and Basic Queries
Week 5: Data Retrieval and Filtering with SQL
Week 6: Principles of Data Visualization and Overview of Tools
Week 7: Analysis and Practical Examples with Excel
Week 8: Dashboard and KPI Design with Tableau and Power BI
Week 9: Dashboard and KPI Design with Tableau and Power BI
Week 10: Introduction to Machine Learning and Artificial Intelligence
Week 11: Business Applications of Artificial Intelligence and Machine Learning
Week 12: Integration of AI and Analytics into ERP Systems
Tentative Assesment Methods
• Midterm 20 %
• Final 30 %
• Homework 30 %
• Project 20 %
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