A curated collection of projects built for academic coursework and personal exploration — spanning backend logic, database design, AI fundamentals, and browser tooling. Each project demonstrates core competencies across multiple languages and paradigms.
Projects/
├── 🐍 Python Projects/ # AI & algorithm implementations (Harvard CS50 AI)
├── 🗄️ SQL Projects/ # Database design & query engineering
├── 🔷 C# Projects/ # Desktop application with .NET (WinForms)
└── 🌐 Chrome Extensions/ # Browser productivity tools (Manifest V3)
Harvard CS50's Introduction to Artificial Intelligence with Python
A series of hands-on projects exploring search algorithms, knowledge representation, machine learning, natural language processing, and neural networks.
| Project | Topic | Concepts |
|---|---|---|
attention |
Natural Language Processing | Transformer attention mechanisms, masked self-attention visualization |
crossword |
Constraint Satisfaction | Backtracking search, arc consistency, constraint propagation |
degrees |
Search Algorithms | Breadth-first search, Six Degrees of Kevin Bacon |
heredity |
Probability | Bayesian networks, joint probability, genetic inheritance modeling |
knights |
Knowledge & Logic | Propositional logic, model checking, Knights & Knaves puzzles |
minesweeper |
Knowledge & Logic | Propositional logic, knowledge-based AI agent for Minesweeper |
nim |
Reinforcement Learning | Q-learning, training an AI to play the game of Nim |
pagerank |
Probability | Random surfer model, iterative PageRank algorithm |
parser |
Natural Language Processing | Context-free grammars, sentence parsing, noun phrase chunking |
shopping |
Machine Learning | k-Nearest Neighbors (kNN), purchase prediction from user data |
tictactoe |
Adversarial Search | Minimax algorithm, alpha-beta pruning, optimal game AI |
traffic |
Neural Networks | TensorFlow/Keras, convolutional neural networks (CNNs), traffic sign classification |
- Language: Python 3
- Libraries: TensorFlow, Keras, scikit-learn, nltk, Pillow
- Course: CS50 AI — Harvard University
A relational database designed to manage and track workout information, including user progress, exercises, and workout sessions.
Features:
- Full CRUD operations for users, workouts, exercises, and progress tracking
- Calorie tracking per workout session
- Optimized queries with indexes on key columns
- Custom views:
specific_user,workout_details,user_total_calories - Entity-relationship diagram included
Schema Overview:
┌──────────┐ ┌──────────────┐ ┌──────────────┐
│ Users │────▶│ Progress │◀────│ Workouts │
│ │ │ │ │ │
│ user_id │ │ progress_id │ │ workout_id │
│ username │ │ user_id (FK) │ │ name │
│ age │ │ workout_id │ │ date │
│ gender │ │ calories │ │ duration │
└──────────┘ └──────────────┘ └──────┬───────┘
│
┌──────▼───────┐
│ Exercises │
│ │
│ exercise_id │
│ name │
│ category │
│ difficulty │
└──────────────┘
Files: schema.sql · queries.sql · DESIGN.md · diagram.png
A SQL project modeling a college management system with student and course data relationships.
Files: Project.sql
- Database: SQLite
- Course: CS50 SQL — Harvard University
A Windows Forms (.NET) desktop application that helps users determine if they may be experiencing the "Titanic Syndrome" through an interactive survey system. The application supports both personal and organizational assessments.
Features:
- 🔐 Offline login/registration system
- 🗄️ Local database for storing user information
- 📝 Interactive multi-step survey with change assessment categories:
- Anticipated Change — planned and expected transitions
- Desired Change — changes you want to happen
- Incremental Change — small, gradual shifts over time
- 📊 Summary and results page with assessment outcomes
- 🎨 Custom UI elements including styled dropdowns and branded components
Screenshots included in the project folder — covering login flows, survey screens, and result summaries for both personal and organizational modes.
- Language: C# (.NET Framework)
- UI: Windows Forms (WinForms)
- IDE: Visual Studio
A lightweight Chromium extension that strips all formatting from selected text, giving you clean plain-text copies every time.
Features:
- ✅ Right-click context menu: "Copy as Plain Text"
- ✅ Popup button for one-click plain text copying
- ✅ Strips bold, italic, colors, fonts — everything
- ✅ Works on all Chromium-based browsers (Chrome, Edge, Brave, Opera GX, Vivaldi)
Technical Details:
- Manifest V3
- Permissions:
clipboardWrite,clipboardRead,contextMenus,scripting,activeTab,tabs - Background service worker architecture
- Languages: JavaScript, HTML, CSS
- Platform: Chrome Extensions API (Manifest V3)
C# ████████████████████████░░░░░░░░░░░░░░░░░░░░░░ 48.2%
Python ████████████████████░░░░░░░░░░░░░░░░░░░░░░░░░░ 39.6%
PureBasic ███░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 6.1%
HTML ██░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 4.2%
JavaScript █░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 1.8%
TSQL ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 0.1%
# Clone the repository
git clone https://github.com/Synergy738/Projects.git
# Navigate to any Python project
cd "Projects/Python Projects/tictactoe"
# Install dependencies (if requirements.txt exists)
pip install -r requirements.txt
# Run the project
python runner.py# Navigate to the SQL project
cd "Projects/SQL Projects/Harvard_Final_Project"
# Create and populate the database
sqlite3 workout.db < schema.sql
# Run sample queries
sqlite3 workout.db < queries.sql1. Open TitanicSyndrome_ver4/ in Visual Studio
2. Build the solution (Ctrl + Shift + B)
3. Run the application (F5)
1. Open chrome://extensions/ in your browser
2. Enable "Developer mode"
3. Click "Load unpacked"
4. Select the Chrome Extensions/plaincopy/ folder
This repository is open source. Feel free to explore the code, learn from it, and adapt it for your own projects.
Built with curiosity and caffeine ☕ by Blu Dennis