Business Analytics

Fall

Module 1: 

BAN 827 Descriptive Analytics (Abdullah Daşçı): This course aims to provide a review of methods for statistical inference, and develop an understanding of how these tools can be applied in a variety of business problems. The emphasis of this course would be on applications, through practical examples and cases. A variety of statistical software will be introduced. Topics covered include descriptive statistics, probability distributions, hypothesis testing, regression, design of experiments and analysis of variance.

BAN 835 AI-Assisted Coding for Data Analytics (Altuğ Tanaltay): This course teaches the fundamental ideas to clean, manipulate, process, and analyze data using Python with the support of AI tools. Following a review of programming fundamentals and Python basics, students will learn to write, test, and debug code efficiently with AI assistance—using chatbots and AI-powered notebooks to generate code, obtain explanations, and accelerate development. The course involves hands-on coding exercises across real-world case studies, including working with files and documents, automating tasks, consuming APIs, and building LLM-powered applications. It serves as both an introduction to data analytics and a practical foundation for AI-assisted scientific computing.

Module 2: 

BAN 805 AI and Machine Learning Fundamentals for Business (Altuğ Tanaltay) : Artificial Intelligence (AI) is reshaping how businesses extract insights from data. This course introduces the fundamentals of AI and machine learning for business analytics through two integrated pillars: coding with AI and building machine learning models. Students use AI tools in notebook environments to generate code, obtain explanations, and analyze data — making coding accessible while developing genuine analytical competency. Machine learning topics include exploratory data analysis, regression, classification, and ensemble methods applied to real business problems, along with model evaluation, bias-variance tradeoff, and regularization techniques.

BAN 831 Data Warehousing and Business Intelligence (Mehmet Yasin Ulukuş) : This course introduces the basics of structured data modeling, gain practical SQL coding experience, and develop an in-depth understanding of data warehouse design and data manipulation. It also allows working with large data sets in a data warehouse environment to create dashboards and introduces a variety of business intelligence solutions.

Spring

Module 3: 

BAN 801 Marketing Analytics (Vahid Karimi Motahhar) : This course is about generating marketing insights from empirical data in such areas as segmentation, targeting and positioning, satisfaction management, customer lifetime analysis, customer choice, and product and price decisions using conjoint analysis. This will be a hands-on course based on the Marketing Engineering approach and Excel software

BAN 821 Optimization & Simulation (Can Akkan) : This course introduces the basic principles and techniques of mathematical modeling that will aid managerial decisions. Students will learn how to develop analytical models and use techniques such as linear and mixed integer programming, Monte Carlo simulation, discrete-event simulation and decision trees. The applications are on models that are widely used in diverse business functional areas.

Module 4: 

BAN 892 Applied AI for Business Analytics (Altuğ Tanaltay) : This course is tailored to professional business analytics students seeking to apply cutting-edge AI methods to real-world business problems. Building on foundational skills in statistics, SQL, and Python, students develop advanced supervised and unsupervised models spanning clustering, dimensionality reduction, text mining, recommendation systems, deep learning, and generative AI. A key feature of the course is the use of vibe coding — leveraging AI-assisted development environments to rapidly prototype and deploy sophisticated models. Students engage with applied research topics across disciplines and are supported in the development of their graduation projects.

BAN 809 Project Management in Analytics (Dursun Delen) : This course introduces students to the theory and practice of project management. This course examines the management of complex projects and the tools are available to assist managers with such projects. Some of the specific topics we will discuss include project life cycle models, work break down structure, organization break down structure, cost break down structure, graphical presentations and precedence diagramming, network analysis and scheduling techniques, concepts of system life cycle costing, and cost estimation methods and trade-off analysis, risk management, and monitoring and control. 

Module 5:

BAN 807 Financial Analytics (Yasin Kütük) : An introduction to methods and tools useful in decision-making in the financial industry, including: macroeconomic event studies, analysis of term structures, Morningstar equity data, style analysis, credit card receivables, trading analytics, execution algorithms, etc. This course blends easy-to-use statistical tools with complex machine learning tools and algorithms to equip the participants with the requisite skill set in analyzing data.

BAN 840 Digital Transformation and Innovation (İlker Altıntaş) : Digital transformation is blurring the boundaries between cyber and physical systems, creating strong synergies across industries. To sustain and enhance competitiveness, decision makers must understand the technologies, approaches, and best practices driving this shift. In today’s global environment, innovation has become as critical as traditional operational priorities such as cost, quality, flexibility, and delivery. This course provides an in-depth exploration of key concepts, trends, and applications of digital transformation, supported by case studies and real-world best practices.

BAN 872 Business Simulation (Aras Can Aktan) : This course provides an opportunity for the participants to integrate knowledge and experience through a computer-based simulation environment. As student teams compete, they develop a deeper understanding of how the various functional areas of management (finance, marketing, production) are integrated. 

European Credits Transfer System (ECTS) : Please click here for more information.

It is a part-time program consisting of 5 modules, each lasting 7 weeks. The courses are conducted in English.

Location :

The Business Analytics Program is specifically designed to allow working participants to attend classes without disrupting their professional lives. Classes are held on Tuesday and Thursday evenings from 19:00 to 22:00 and on Saturdays from 09:30 to 16:30. Some elective courses can be scheduled on other weekday evenings (Monday, Wednesday or Friday)

All classes take place at the Altunizade Digital Campus, which stands out for its easily accessible location. [Click here for transportation details.]

As the first of its kind in Turkey, Sabancı University’s Altunizade Digital Campus serves as a hub that brings together technology, business, and academia with its cutting-edge technological infrastructure. The campus creates an ecosystem that maximizes the opportunities offered by the digital world through education, research, and industry collaborations.