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Recent News:
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First lecture on January 25, 2021. In-person instruction for registered students will be from February 8, 2021.
First two weeks of lectures will conducted via Webex.
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Course Description:
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Business analytics enables organizations to leverage large volumes of data in order to make more informed decisions. It encompasses a range of approaches to integrating, organizing, and applying data in various settings. This course develops an understanding of concepts in business analytics and data manipulation. In particular, through hands-on experience with a range of techniques students will learn to work with large data sets, analyse trends and segmentations and develop models for prediction and forecasting.
Towards this goal, students will :
- learn how to approach a new analytics challenge and ask the right questions
- construct and work with large data sets
- understand a range of models and techniques for data manipulation and prediction
- learn to visualize and present data insights.
This course is part of the MS program in Business Analytics and builds on foundations learned in the Fall semester.
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Prerequisites:
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It is preferable that students have had background in quantitative methods for business as well as coding experience in Python but not compulsory.
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Office hours:
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Location: Webex
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Contact Info:
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manikl@rpi.edu
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TA:
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Yuanyuan Liu
Email: liuy55@rpi.edu
Office hours: Friday 11 am -- 1 pm
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Grading:
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| Exam: | 40% | in-class and individual test, covering the material studied up to this date. |
| Project: | 25% | hands-on project will ensure you are able to apply what we have covered throughout the course. The project will be completed in groups of 3 students. More information will follow |
| Assignments: | 30% | there will be three group assignments, shown in the schedule on the next page. |
| Class participation: | 5% | Active class participation |
Missing an assignment or a test without prior approval from the instructor will result in a grade of zero (0). There will be no opportunities for extra credits or make-up assignments.
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Communication:
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For any course-related discussions, lecture materials and announcements, please check the blackboard or the website.
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Syllabus:
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Course syllabus can be downloaded from here.
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Textbooks:
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