AI Capstone Collaboration for Real-World Solutions

COMP 385
Fermé
Contact principal
Centennial College
Toronto, Ontario, Canada
Elle / Elle
Employer Relations Coordinator
(10)
6
Chronologie
  • janvier 21, 2025
    Début de Expérience
  • janvier 21, 2025
    Project Proposal and scope
  • février 15, 2025
    Progress report #1
  • février 22, 2025
    Prototype demonstration #1
  • mars 15, 2025
    Progress report #2 & Prototype demonstration
  • mars 29, 2025
    Final report & Final demo
  • avril 12, 2025
    Fin de Expérience
Expérience
6/8 match de projet
Dates fixées par le Expérience
Compagnies privilégiées
Ontario, Canada
Tout type de Compagnie
N'importe qu'elle industrie

Portée de Expérience

Catégories
Technologie de l'information Développement de logiciels Intelligence artificielle
Compétences
effective communication communication constructive feedback research design scalability technical report artificial intelligence innovation data analysis
Objectifs et capacités de Apprenant.es

Centennial College’s AI Capstone Project learners collaborate to research, design, and develop AI-driven applications that solve real-world problems. They bring expertise in AI techniques and data analysis to deliver innovative and scalable applications integrated with AI capabilities. Throughout this experience, students will develop their skills in ethical AI practices, advanced programming, and effective communication with both technical and non-technical stakeholders.


Students will primarily focus on building end-to-end AI solutions and capabilities and proof of concepts.

Students may have limited UX/UI, front-end/back-end development, cloud deployment, etc. capabilities.


Employers engaging in this collaboration are expected to provide regular communication and guidance, share relevant project information, attend a virtual final presentation, and offer constructive feedback on the project progress and final demonstration using the Riipen platform.


Employers are expected to provide data with full metadata, and clean data for the projects as much as possible.


Apprenant.es

Apprenant.es
Premier cycle universitaire
Niveau Débutant, Intermédiaire
20 Apprenant.es dans le programme
Projet
50 heures par Apprenant.e
Les Educateur.trices affectent les Apprenant.es à des projets
Équipes de 4
Résultats et livrables attendus

Employers will receive the following deliverables at the end of this collaboration:

  • A final technical report detailing the AI application, including data analysis, model selection, and recommendations for practical implementation.
  • A final demonstration of the AI application, featuring a code walk-through and insights on the AI capability’s performance and scalability.


Chronologie du projet
  • janvier 21, 2025
    Début de Expérience
  • janvier 21, 2025
    Project Proposal and scope
  • février 15, 2025
    Progress report #1
  • février 22, 2025
    Prototype demonstration #1
  • mars 15, 2025
    Progress report #2 & Prototype demonstration
  • mars 29, 2025
    Final report & Final demo
  • avril 12, 2025
    Fin de Expérience

Exemples de projets

Ideal projects for this experience require integrating AI capabilities within applications to solve complex, data-driven problems. There is also a special interest in projects that focus on Generative AI. These projects offer learners the chance to explore AI models, conduct data analysis, and develop impactful and industry-relevant solutions.

  • Predictive Maintenance System: Develop an AI capability that analyzes historical data to predict machinery breakdowns and optimize maintenance schedules.
  • Customer Sentiment Analysis Tool: Build an AI tool to analyze customer feedback and online reviews, providing insights into customer sentiment for business improvement.
  • Automated Inventory Management: Create an AI-driven inventory system that predicts demand, tracks stock levels, and suggests optimal restocking strategies.
  • Healthcare Diagnostic Assistance: Design an AI application that supports diagnostic processes by analyzing patient data and providing predictive health insights.
  • Smart Recommendation Engine: Build a recommendation system that uses AI to analyze user preferences and behavior, delivering personalized product or content suggestions.



Critères supplé mentaires pour Compagnie

Les Compagnies doivent répondre aux questions suivantes pour soumettre une demande de jumelage pour cette Expérience:

  • Q1 - Choix multiple
    If matched, will this project be reserved solely to the Centennial College student team?  *
    • Yes
    • No
    • Unsure
  • Q2 - Texte court
    How many team members are committed to providing supervision/mentorship to students for the duration of the project?  *
  • Q3 - Texte long
    Will you be using Riipen or another platform to directly communicate with the student team?  *
  • Q4 - Texte long
    Please list any tools, programs or languages your project requires?  *
  • Q5 - Texte court
    Do you or your team members have flexibility to schedule touch point meetings during student class times?  *