Program Overview

Introduction to the Business Analytics for Professionals Program

The Business Analytics for Professionals Program at Sabanci University is designed to educate professionals who can help private sector and public institutions better understand their business performance in competitive environments and develop data-driven strategies.

Program Objectives and Learning Outcomes

This master's program leverages insights from various disciplines to enhance data-driven decision-making processes in the business world. Participants will:

• Learn to make data- and model-based business decisions.
• Gain the ability to develop solutions for real-world business problems.
• Utilize analytical approaches to improve organizational efficiency.

Program Structure

The program consists of 5 modules, each lasting 7 weeks. The language of education is English.

Location

The Business Analytics for Professionals 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. All classes take place at the Altunizade Digital Campus.

Application Process

Applicants to the PBAN Program should have a bachelor’s degree and an interest in the area. Candidates who are committed to their personal development and who are willing to invest their twelve months to learning in the program are preferred.

Application Requirements

• Copy of the Diploma: (or graduation certificate if you have not graduated yet) from an undergraduate institution.
• One Photograph: Candidates must upload a passport-sized photo to the online system.
• Official Transcript: An official document issued by the registrar of the candidate's previous institution showing all courses taken and grades received by the candidate.
• Curriculum Vitae: Candidates must submit an up-to-date Curriculum Vitae (resume).
• Two Letters of Recommendation: The writers of recommendation letters are expected to upload them to the online system.
• Statement of purpose: It should be uploaded under "Documents" in the online application system.
• English Proficiency: Candidates will be assessed for their English proficiency during the interview stage.

English Proficiency Requirements

• TOEFL IBT: 83
• PTE: 56
• CAE: B
• CPE: C
• YDS-EYDS-YÖKDİL: 69

Interview Process

After reviewing the documents of applicants to the program, candidates who are deemed suitable are invited for an interview.

Tuition Fee

The tuition fee is payable in installments at the beginning of each term. For those students whose tuition is at least partially paid by the institution they are working for, payments should be made at the beginning of each semester in two equal installments.

Student Profile

• Industries:
• Gender: 70% Female, 30% Male
• Average Age: 30
• Majors:

Alumni

The program has a strong network of alumni, with graduates such as Şan Yeltekin, Cihan Altay, and Hakan Durakoğlu.

Program Details

Course Category

Modules

Module 1

• BAN 827 Descriptive Analytics: 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.
• BAN 835 Computational Tools and IT for Analytics: This course explores both the functional and technical environment for the creation, storage, and use of the most prevalent source and type of data for business analysis.

Module 2

• BAN 805 Predictive Analytics: This course introduces basic concepts and models of supervised and unsupervised statistical learning models.
• BAN 830 Digital Enabled Business Transformation: This course delves into how data, AI, and digital technologies are reshaping business models and entire industries.

Module 3

• BAN 801 Marketing Analytics: 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.
• BAN 831 Data Warehousing and Business Intelligence: 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.

Module 4

• BAN 821 Optimization & Simulation: This course introduces the basic principles and techniques of mathematical modeling that will aid managerial decisions.
• BAN 809 Project Management in Analytics: This course introduces students to the theory and practice of project management.

Module 5

• BAN 892 Applied Advanced Analytics: This is a hands-on course to equip students with ways to prepare a culminating project that follows a multifaceted approach in business analytics.
• BAN 807 Financial Analytics: An introduction to methods and tools useful in decision-making in the financial industry.
• BAN 872 Business Simulation: This course provides an opportunity for the participants to integrate knowledge and experience through a computer-based simulation environment.

Program Outcomes

• Develop the ability to use critical, analytical, and reflective thinking and reasoning
• Reflect on social and ethical responsibilities in his/her professional life.
• Gain experience and confidence in the dissemination of project/research outputs
• Work responsibly and creatively as an individual or as a member or leader of a team and in multidisciplinary environments.
• Communicate effectively by oral, written, graphical and technological means and have competency in English.
• Independently reach and acquire information, and develop appreciation of the need for continuously learning and updating.

Program Specific Outcomes

• Demonstrated understanding of data-driven decision modeling and analysis concepts/frameworks.
• Knowledge of and hands-on experience with fundamentals of business analytics, management information systems, statistical and prediction models.
• Ability to transform complex data into valuable insight and resulting value-adding actions.
• Skills in hands-on data-mining tools and techniques.
• Exposure to the analytical methods in basic business disciplines such as marketing, operations, and finance.