Enhance Your Business with Data-Driven Insights
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Timeline
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September 30, 2025Experience start
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December 2, 2025Experience end
Experience scope
Categories
Data visualization Data analysis Data modelling Data scienceSkills
data preprocessing exploratory data analysis python (programming language) machine learning data analysisThe 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.
Learners
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
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September 30, 2025Experience start
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December 2, 2025Experience end
Project examples
To ensure the best fit for our learners and the success of your project, we suggest the following types of projects:
- Sales/Demand Forecasting: Develop predictive models to forecast future sales based on historical data.
- Churn Prediction: Implement machine learning models to predict customer churn and suggest retention strategies.
- Social Media Sentiment Analysis: Analyze social media data to gauge public sentiment about your brand and products.
- Market Basket Analysis: Use transactional data to identify customer purchasing behaviors.
- Customer Segmentation: Analyze customer data to identify distinct segments and tailor marketing efforts to each group.
Additional company criteria
Companies must answer the following questions to submit a match request to this experience:
Main contact

Timeline
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September 30, 2025Experience start
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December 2, 2025Experience end