Applied machine learning and AI projects from the Post Graduate Program in Artificial Intelligence and Machine Learning: Business Applications at Texas McCombs / Great Learning. Each project addresses a real-world business problem with a practical, production-minded approach.
Project Portfolio
Medical Assistant
Retrieval-Augmented Generation (RAG) for Healthcare
A RAG-based AI solution that leverages medical manuals to address information overload and support clinical decision-making. Built to help healthcare professionals quickly retrieve relevant medical information and generate accurate, context-aware responses.
Tech Stack:
RAG LLM Prompt Engineering
ReneWind
Predictive Maintenance for Wind Turbines
Neural-network classification models for wind turbine generator failure prediction. Designed to enable proactive maintenance strategies that reduce downtime and optimize operational efficiency in renewable energy infrastructure.
Tech Stack:
Neural Networks Classification
EasyVisa
Visa Approval Prediction with Ensemble Methods
A predictive modeling solution for visa applicant outcomes using ensemble learning techniques. Identified key decision factors and generated actionable business recommendations to streamline the visa approval workflow.
Tech Stack:
Bagging Boosting Stacking
HelmNet
Construction Safety Compliance via Computer Vision
A computer vision solution for construction safety compliance, using CNNs to classify workers with and without helmets. Designed to automate safety monitoring and reduce workplace hazards on construction sites.
Tech Stack:
Computer Vision CNN
Program Details
Post Graduate Program in Artificial Intelligence and Machine Learning: Business Applications
Texas McCombs School of Business / Great Learning
This program focuses on the practical application of AI and ML to real business problems, covering areas including natural language processing, computer vision, predictive analytics, deep learning, and AI product strategy.
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