Enhance Your Business with Data-Driven Insights

BUSADMIN O712
Closed
Project Coordinator, Academic Experiential Learning, DeGroote School of Business
5
Timeline
  • October 15, 2024
    Experience start
  • October 15, 2024
    Kick-off meeting
  • December 13, 2024
    Final Report
  • December 14, 2024
    Experience end
Experience
2 projects wanted
Dates set by experience
Preferred companies
Canada
Any company type
Any industries
Categories
Data visualization Data analysis Data modelling Data science
Skills
data preprocessing exploratory data analysis python (programming language) machine learning data analysis
Student goals and capabilities

The DeGroote School of Business is proud to present a unique opportunity through our course, Data Analytics with Python. Our students in our Master of Business Administration program, will be equipped with comprehensive skills in Python programming and data analytics. They are prepared to tackle real-world business challenges by performing data preprocessing, visualization, exploratory data analysis, and building statistical and machine learning models. This hands-on experience is designed to produce data-driven business decisions and valuable managerial insights.


Employers participating in this experience are expected to engage in communication with the learners, provide necessary information for the project's success, attend the final presentation virtually, and offer constructive, professional feedback through the Riipen platform. Your guidance will be instrumental in shaping the future of these aspiring data analysts.

Students
Graduate
Beginner, Intermediate levels
35 students
Project
25 hours per student
Administrators assign students to projects
Teams of 4
Expected outcomes and deliverables

At the end of this collaboration, employers will receive:

  • A comprehensive final report detailing the main findings and actionable recommendations proposed by the student teams.
  • A final presentation where learners will present the project results and answer any questions, providing a thorough understanding of the data-driven insights generated.


Project timeline
  • October 15, 2024
    Experience start
  • October 15, 2024
    Kick-off meeting
  • December 13, 2024
    Final Report
  • December 14, 2024
    Experience end
Project Examples

To ensure the best fit for our learners and the success of your project, we suggest the following types of projects:


  1. Sales/Demand Forecasting: Develop predictive models to forecast future sales based on historical data.
  2. Churn Prediction: Implement machine learning models to predict customer churn and suggest retention strategies.
  3. Social Media Sentiment Analysis: Analyze social media data to gauge public sentiment about your brand and products.
  4. Market Basket Analysis: Use transactional data to identify customer purchasing behaviors.
  5. Customer Segmentation: Analyze customer data to identify distinct segments and tailor marketing efforts to each group.


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

What type of data will be available for the students to work with?

Is the data clean and ready for analysis?

Are you able to commit to timely communication and feedback throughout the project duration?

Can you attend a virtual final presentation to review the project outcomes and provide feedback?