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msc data analytics and artificial intelligence projects

Open Closing on June 15, 2025
London Metropolitan University
London Metropolitan University
London, England, United Kingdom
Dipo Dunsin
Senior Lecturer
1
Experience
10 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any company type
Any industries

Experience scope

Categories
Machine learning Artificial intelligence Data analysis Data modelling
Skills
statistical analysis data processing machine learning algorithms data analysis predictive modeling technical documentation artificial intelligence data visualization dashboard reinforcement learning
Learner goals and capabilities

This experience is designed for MSc students specializing in artificial intelligence and data analytics. These learners possess a strong foundation in machine learning algorithms, data processing, and statistical analysis. They are eager to apply their skills to real-world projects, focusing on extracting actionable insights from complex datasets. By collaborating with industry professionals, students can enhance their problem-solving abilities and contribute innovative solutions to data-driven challenges.

Learners

Learners
Post-graduate
Intermediate levels
50 learners
Project
600-800 hours per learner
Learners self-assign
Individual projects
Expected outcomes and deliverables

Example of deliverables could include these:

  • Comprehensive data analysis reports with actionable insights
  • Predictive models using machine learning algorithms
  • Data visualization dashboards for stakeholder presentations
  • Automated data processing pipelines
  • Technical documentation and user manuals
Project timeline
  • June 15, 2025
    Experience start
  • August 31, 2025
    Experience end

Project Examples

Requirements
  • Developing a predictive model for customer churn in a retail company
  • Creating a data visualization dashboard for sales performance analysis
  • Designing an automated pipeline for processing and analyzing social media data
  • Building a recommendation system for an e-commerce platform
  • Conducting sentiment analysis on customer feedback for a service provider
  • Implementing a machine learning model to forecast product demand
  • Analyzing sensor data to optimize manufacturing processes
  • Evaluating the effectiveness of marketing campaigns through data analytics