Selkirk College
Selkirk College
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AI & Data Science: Machine Learning and Data Visualization for Business Solutions

AISC 2000 & AISC 2001
Open Closing on March 11, 2025 / 2 spots left
Loyalist College
Loyalist College
Belleville, Ontario, Canada
Baba' Giwa
Professor
3
Timeline
  • March 17, 2025
    Experience start
  • April 21, 2025
    Experience end
Experience
2 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any company type
Any industries

Experience scope

Categories
Machine learning Artificial intelligence Data visualization Data analysis Data modelling
Skills
predictive analytics data visualization python (programming language) data presentation data storytelling artificial intelligence power bi tableau (business intelligence software) exploratory data analysis
Learner goals and capabilities

Experience Overview:

This experience enables students to apply machine learning algorithms and data visualization techniques to solve real-world business problems. Through hands-on projects, students will develop predictive models, analyze data trends, and communicate insights effectively using visualization tools. Businesses will gain valuable, data-driven insights tailored to their operational needs.


Learner Capabilities:

Students will be able to:

  • Develop and apply machine learning models for predictive analytics.
  • Use supervised and unsupervised learning to identify patterns and insights.
  • Optimize models by balancing accuracy, efficiency, and computational cost.
  • Leverage AI to support decision-making through data-driven recommendations.
  • Design compelling data visualizations for storytelling and business intelligence.
  • Utilize industry-standard tools (e.g., Python, Power BI, Tableau, Matplotlib, Plotly).
  • Present findings effectively through reports, dashboards, and oral presentations.


Learners

Learners
Certificate
Beginner, Intermediate levels
16 learners
Project
25 hours per learner
Educators assign learners to projects
Teams of 4
Expected outcomes and deliverables

Students will work on a data-driven AI consulting project, culminating in:

  • Predictive AI Model: A machine learning model trained on real-world data to identify trends and make data-driven recommendations.
  • Data Visualization Dashboard: A business intelligence dashboard (e.g., Power BI, Tableau) for stakeholder insights.
  • Technical Report & Business Strategy: A comprehensive report explaining methodology, findings, and business applications.
  • Final Presentation: A professional presentation showcasing AI-driven insights and actionable recommendations.


Project timeline
  • March 17, 2025
    Experience start
  • April 21, 2025
    Experience end

Project Examples

Requirements

Ideal Employer Profile:

Organizations looking to leverage AI, predictive analytics, or business intelligence for strategic decision-making. Ideal partners include, but not limited to, businesses in finance, construction, healthcare, retail, marketing, or logistics that have data-driven challenges.


Project Examples:

  • Customer Churn Prediction: Using machine learning to predict customer retention and propose intervention strategies.
  • Sales Forecasting & Trend Analysis: Predicting sales based on historical data and visualizing future trends.
  • Anomaly Detection for Fraud Prevention: Identifying irregularities in financial transactions to detect fraud.
  • Healthcare Data Analytics: Using AI to analyze patient data and predict health outcomes.
  • Supply Chain Optimization: Using predictive models to improve logistics and inventory management.

Additional company criteria

Companies must answer the following questions to submit a match request to this experience:

  • Q1 - Text short
    Be available for a quick phone/virtual call with the instructor to initiate your relationship and confirm your scope is an appropriate fit for the experience.
  • Q2 - Text short
    Provide a dedicated contact person who is available for weekly/bi-weekly drop-ins to address learners’ questions as well as periodic messages over the duration of the project.  *
  • Q3 - Text short
    Provide an opportunity for learners to present their work and receive feedback.  *
  • Q4 - Text short
    Provide relevant information and/or data as needed for the project.  *
  • Q5 - Text long
    How is your project relevant to the experience?