2024 Spring Data Mining for Data Analytics
General
- Post-graduate; 1st year
- 25 learners; teams of 4
- 50 hours per learner
- Dates set by experience
- Educators assign learners to projects
Preferred companies
- 6 projects wanted
- Anywhere
- Academic experience
- Any company type
- Any industries
Categories
Skills
Project timeline
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March 8, 2024Experience start
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April 22, 2024Experience end
Overview
- Details
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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 Tableau 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.
- Learner skills
- Python (programming language), Machine learning, Predictive modeling, Spring data, Data modeling, Consulting, Tableau (business intelligence software), Decision making
- Deliverables
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Final deliverables will include:
- A slide deck with conclusions and recommendations for a 15 to 30-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 Examples
Example projects include, but are not limited to:
- Customer Analytics and Customer Behavioural models
- Bioinformatics models
- Computer Vision models
- Financial Data for predictive model
- Or only have data and do not have ideas how to link up with your business
Additional company criteria
Companies must answer the following questions to submit a match request to this experience:
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.
Be available for an introductory session at the beginning of the project (in person or virtual).
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.
Provide students with the data necessary to conduct their data mining analysis.