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An advanced course in business analytics focusing on data mining techniques and practical applications using RapidMiner and Tableau. Students will learn to leverage analytics for decision-making and gain skills in predictive modeling and pattern discovery.

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MIS571: Business Analytics Software and Applications II Coursework

This repository contains my coursework, including assignments, quizzes, and project files for the "Business Analytics Software and Applications II" course (MIS571) I am taking as part of my studies. Below you'll find details about the course content, instructor information, and links to my projects and exercises.

Instructor Information

Course Description

This course introduces students to business analytics concepts and tools. It covers both supervised and unsupervised data mining techniques such as regression, classification, clustering, and data visualization. Software such as RapidMiner and Tableau will be used for hands-on exercises.

Course Structure

  • Lectures: Held in person every M/W from 3:00 PM – 4:15 PM.
  • Assignments & Quizzes: 5 assignments and 5 quizzes are scheduled throughout the semester to assess comprehension.
  • Project: A group project involving data mining and business analytics tools, with a final presentation.

Repository Contents

  • Lecture Notes/ - Contains PDFs of lecture slides and notes.
  • Assignments/ - Completed assignments as per course requirements.
  • Quizzes/ - Screenshots and reflections on quiz feedback.
  • Project/ - Final group project files and documentation.

Tools Used

  • RapidMiner - For data mining, machine learning, and predictive analytics tasks.
  • Tableau - For data visualization and analysis.

Prerequisites

  • Basic knowledge of data science and business analytics is recommended but not required.

Contact

For any queries regarding this repository or the projects, feel free to contact me via email.

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An advanced course in business analytics focusing on data mining techniques and practical applications using RapidMiner and Tableau. Students will learn to leverage analytics for decision-making and gain skills in predictive modeling and pattern discovery.

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