Data Mining & Analytics

COMP 5353:
Closed
North American University
Stafford, Texas, United States
Associate Professor of Computer Science
2
Timeline
  • January 23, 2020
    Experience start
  • January 30, 2020
    Project Scope Meeting
  • March 5, 2020
    First Draft of the Project
  • April 30, 2020
    Final presentation
  • May 2, 2020
    Experience end
Experience
1/1 project matches
Dates set by experience
Preferred companies
Anywhere
Any
Any industries

Experience scope

Categories
Information technology Data analysis Sales strategy Marketing strategy
Skills
python r data mining big data sas em
Learner goals and capabilities

A group of student-consultants at North American university will analyze data sets using state-of-the-art technologies to identify trends, and submit recommendations based on predictive models that can enhance decision-making in your organization.

Learners

Learners
Undergraduate
Any level
50 learners
Project
40 hours per learner
Learners self-assign
Teams of 4
Expected outcomes and deliverables

Final deliverables will include:

  • A slide deck with conclusions and recommendations for a 15-minute consulting presentation.
  • A written report with details of the predictive models that were developed, including insights and overall recommendations that are inferred from such models.
  • All applicable source code.
Project timeline
  • January 23, 2020
    Experience start
  • January 30, 2020
    Project Scope Meeting
  • March 5, 2020
    First Draft of the Project
  • April 30, 2020
    Final presentation
  • May 2, 2020
    Experience end

Project Examples

Requirements

How is your business handling business analytics? Students at North American University will act as consultants using Data Mining to help identify patterns in your organizations data. Data Mining for Business Analytics is becoming one of the fastest-growing areas to help scale your business.

Beginning in late January, a class of student-consultants will spend an entire semester performing a thorough investigation of data sets to tackle a managerial question. Tools such as SAS EM, and Python packages will be leveraged for data modeling, machine learning, and visualization.

Based on the information that you provide, groups will develop predictive models and managerial insights into key aspects of your organization. Each team will propose solutions and implementation strategies to improve your decision-making processes and outcomes.

Example projects include, but are not limited to:

  • Analysis of customer segmentation relative to different products and services, to enhance marketing campaigns and refocus your products/services.
  • Investigate predictive models to understand trends in sales, attrition rates, and profits that impact your business.
  • Propose new ways to visualize data through tables and plots that can provide new insights for managers.
  • Reduce customer churn.
  • Maximize revenue through up-sell and cross-sell.
  • Determine sales trends.
  • Accurately predict customer behaviors.
  • Improve new customer acquisition.

Additional company criteria

Companies must answer the following questions to submit a match request to this experience:

Be available for an introductory session at the beginning of the project (in person or virtual).

Provide students with the data necessary to conduct their data mining analysis.

Minimum of 2-4 interactions with the students in-person or remotely (approximately 4-6 hours over the duration of the project).

Be available for a quick phone call with the organizer to initiate your relationship and confirm your scope is an appropriate fit for the experience.

Provide a dedicated contact who will be available to answer periodic emails or phone calls over the duration of the project to address students questions or provide additional information.