Data Analytics Capstone Project

St. Clair College
Windsor, Ontario, Canada
Instructor
(3)
5
Timeline
  • June 15, 2023
    Experience start
  • August 31, 2023
    Experience end
Experience
3 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any company type
Any industries

Experience scope

Categories
Data visualization Data analysis Data modelling Data science
Skills
python (programming language) sql (programming language) data analysis r (programming language)
Learner goals and capabilities

This capstone course is aimed at enriching student success by combining the knowledge skills and tools students have learned throughout their program. The skills are used to complete a project on a real-world challenge presented by an instructor or an industry partner. Students will use appropriate analytics techniques and tools and best practices to present results to stakeholders. Students are familiar with Excel, Python, R, SQL and variety of other tools from prior coursework.

Learners

Learners
Graduate
Any level
50 learners
Project
50 hours per learner
Learners self-assign
Individual projects
Expected outcomes and deliverables

The project will provide:

  • A final report detailing the problem, attempted solutions, and results, including benchmarks, if applicable.
  • Ideas for next steps in the process based on project outcomes.
Project timeline
  • June 15, 2023
    Experience start
  • August 31, 2023
    Experience end

Project Examples

Requirements

The course provides an opportunity for businesses and learners to collaborate to identify and translate a real business problem into a data analytics problem. The project can be an end-to-end application, including data collection & preparation, analysis, visualization, evaluation against success criteria and possible methods for deployment. Project results/ recommendations will be communicated in a final report.

You should submit a high-level proposal/business problem statement including a clear connection to data analysis, relevant data sets and definitions, a list of acceptable tools (if applicable), and expected deliverables. Business datasets could be provided based on a non-disclosure agreement or in an anonymized/synthetic data format that is relevant to your organization and business problem. The course instructor will review the documents to confirm the scope and timing of the proposed problem and its alignment with the course requirements.