Aaryan Samanta — Capstones, Coursework & Applied AI Projects
Welcome to my portfolio of Capstone projects and coursework from a series of advanced AI and Data Science programs. The work here reflects hands-on, original research and applied projects, and is kept separate from public coursework repositories to protect academic integrity, sensitive data usage, and future publication opportunities.
This repository demonstrates growth across Python programming, statistical analysis, data visualization, supervised learning, NLP, neural networks, and applied deep learning for healthcare.
| 🧠 | 📊 | 🤖 | 🌐 | ⚙️ |
|---|---|---|---|---|
| AI Internship Honors | Data Science Honors | AI Technology Honors | AI Humanities Honors | Machine Learning Honors |
| Supervised learning, decision trees, neural nets & a medical-imaging capstone | Python, EDA, statistics, APIs & visualization | Peer-programmed Python fundamentals & NLP sentiment analysis | Ethics & societal impact of AI capstone | End-to-end ML capstone predicting diabetes risk |
advanced-ai-curriculum/
├── ai-internship-honors/ 🤖 Supervised learning → CNNs → medical imaging capstone
├── ai-technology-honors/ 🧑💻 Python fundamentals & NLP sentiment analysis
├── ai_humanities_honors/ 🌐 AI ethics & humanities capstone (report + slides)
├── data-science-honors/ 📊 Python, EDA, stats, APIs, visualization → capstone
└── machine_learning_honors/ ⚙️ Diabetes prediction capstone (ML pipeline + video)
|
AI Internship Capstone · A Convolutional Neural Network trained to detect signs of pneumonia in chest X-ray images — covering image preprocessing, CNN architecture design, iterative training, and evaluation, documented in a full technical report and slide deck. |
Data Science Capstone · An end-to-end EDA project exploring a real-world healthcare dataset — cleaning, feature exploration, correlation analysis, and actionable insight generation. |
|
Machine Learning Capstone · A full ML pipeline predicting diabetes risk from patient health data, presented alongside a walkthrough video of the project. |
AI Humanities Capstone · A research capstone examining the ethical and societal dimensions of applied AI, delivered as a written report and presentation. |
This repository contains original capstone and research work that is:
- 🚫 Unpublished and not intended for public distribution
- 🔐 Protected to prevent unauthorized reuse or copying
- 🏥 Built using healthcare-adjacent datasets handled with care around research and publication considerations
⚠️ Please do not copy, redistribute, or submit any part of this work as your own — doing so may constitute plagiarism or a violation of academic policy.
Every course folder follows the same structure:
- 📂 A subfolder per assignment or milestone, numbered in learning order
- 📝 A
README.mdexplaining what's inside, the datasets used, and key takeaways - 💻 Source code (
.ipynb/.py) with author headers and documentation