Data Analytics Capstone Project

DAB402
Fermé
St. Clair College
Windsor, Ontario, Canada
Professor
(1)
2
Chronologie
  • janvier 19, 2021
    Début de expérience
  • mai 2, 2021
    Fin de expérience
Expérience
2/5 match de projet
Dates fixées par le expérience
Entreprises privilégiées
N'importe où
Any
N'importe qu'elle industrie

Portée de Expérience

Catégories
Technologie de l'information Analyse des données
Compétences
business analytics data analysis research data analysis, data science concepts, text analytics model development deployment and documentation
Objectifs et capacités de apprenant.es

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.

Apprenant.es

Apprenant.es
Finissant
Tout niveau
8 apprenant.es dans le programme
Projet
150 heures par apprenant.e
Les apprenant.es s'auto-attribuent
Équipes de 5
Résultats et livrables attendus

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.
Chronologie du projet
  • janvier 19, 2021
    Début de expérience
  • mai 2, 2021
    Fin de expérience

Exemples de projets

Exigances

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.

Critères supplé mentaires pour entreprise

Les entreprises doivent répondre aux questions suivantes pour soumettre une demande de jumelage pour cette expérience:

  • Q - Case à cocher
  • Q - Case à cocher
  • Q - Case à cocher
  • Q - Case à cocher