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Semester 2 in Review

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CIS 509: Data Mining 2

This course starts with the necessary programming skills in Python and then building a Recommendation system. Then come to Text Mining and Network Analysis using Python. There are 5 assignments to be submitted in Python code. Towards the end of the course, Big Data Technologies like Hadoop, Kafka, and AWS is taught in brief, with some exercises in AWS as well.

Tools covered: Python, AWS, Hadoop, Kafka

SCM 519: Analytical Decision Modeling II

Using simulation techniques to perform Decision Modelling when there is uncertainty. At the end of the course, there is a team-based case to be solved, an open-ended simulation problem that requires a lot of excel skills.

Tools covered: @Risk and Precision Tree (both are Excel plug-ins)

CIS/SCM 593: Applied Project

A team-based capstone project to implement the skills learned through the course to real-world corporate problems. This course is a Semester-long activity.

MKT 591: Marketing Analytics

The course starts off with basics in the R programming language. Then moves to Marketing concepts and applying different types of analytical methods to Marketing related problems. The course ends with a team-based project where you can choose your dataset and apply the concepts learned in the class.

Tools covered: R, Rstudio

CIS 515: Business Analytics Strategy

A typical business school subject with a focus on case studies to understand the implication of Data Analytics. We learn about Ethics, Privacy and the importance of Soft Skills in the corporate business setting. The class encourages discussion-based learning. The class project includes a venture pitch for an idea that involves Data Analytics.

Tools covered: IBM Watson Analytics