This is a hands-on course to equip students with ways to prepare a culminating project that follows a multifaceted approach in business analytics. The course employs an end-to-end approach by following CRISP-DM (Cross-Industry Standard Process for Data Mining) throughout the module. The course also recapitulates earlier courses in the program and dives into further intricacies of descriptive, predictive and prescriptive analytics.
Applied Advanced Analytics (BAN 892)
2021 Spring
Sabancı Business School
Business Analytics(BAN)
3
10
Enes Eryarsoy enes@sabanciuniv.edu,
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English
Doctoral, Master
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| Programs\Type | Required | Core Elective | Area Elective |
| Business Analytics - Non Thesis | * |
CONTENT
LEARNING OUTCOMES
PROGRAMME OUTCOMES
1. Develop the ability to use critical, analytical, and reflective thinking and reasoning 5
2. Reflect on social and ethical responsibilities in his/her professional life. 5
3. Gain experience and confidence in the dissemination of project/research outputs 5
4. Work responsibly and creatively as an individual or as a member or leader of a team and in multidisciplinary environments. 5
5. Communicate effectively by oral, written, graphical and technological means and have competency in English. 5
6. Independently reach and acquire information, and develop appreciation of the need for continuously learning and updating. 5
1. Develop, interpret and use statistical analyses in decision making. 5
1. Demonstrated understanding of data-driven decision modeling and analysis concepts/frameworks. 5
2. Knowledge of and hands-on experience with fundamentals of business analytics, management information systems, statistical and prediction models. 5
3. Ability to transform complex data into valuable insight and resulting value-adding actions. 5
4. Skills in hands-on data-mining tools and techniques. 5
5. Exposure to the analytical methods in basic business disciplines such as marketing, operations, and finance 5