Python | Data workflows | Payment analytics | Automation systems | Web systems | ML experiments
Practical projects around data cleaning, forecasting, dashboards, APIs, testing, and algorithmic experiments.
Projects are ranked from the most complex and portfolio-relevant work to lighter supporting projects. Public repositories are open; private repositories are shown as locked project cards.
|
Sanitized internal analytics pilot for comparing payment progress, forecasting month-end collections, exporting operational views, and explaining dashboard results with an AI-assisted knowledge layer. Open detailsGoal: monitor collection progress, estimate expected month-end results, and prepare management-ready reporting from payment data. Languages: Python, HTML, CSS, JavaScript. Access: private repository; visible only to approved collaborators. Highlight: forecasting and backtesting logic, multi-country dashboard views, automated Python workflows for data refresh and dashboard rebuilds, operational exports, validation checks, and an AI assistant that answers project-specific dashboard questions. |
|
|
Sanitized production-style Windows automation for scheduled payment-file ingestion, XML validation and normalization, encrypted SQL credential handling, stored-procedure imports, operational logging, and failed-row reporting. Open detailsGoal: replace manual payment-file handling with a controlled import pipeline that validates incoming XML files, normalizes payment records, runs scheduled database imports, and produces recoverable operational reports without exposing internal data. Languages: PowerShell, Windows CMD, T-SQL, XML, HTML, CSS, JavaScript. Access: private/internal project; code and data are not published because the workflow is connected to production infrastructure and payment-processing operations. Highlight: Windows Task Scheduler orchestration, DPAPI-encrypted SQL credential flow, read-only validator mode, XML normalization, SQL stored procedure integration, processed/error folder routing, failed-row CSV reporting, runbook documentation, and an interactive system-flow map. |
|
|
Research framework for comparing AI tools and models for corporate use across security, data privacy, cost, integration fit, output quality, governance, and practical employee workflows. Open detailsGoal: support business AI adoption decisions with a structured evaluation model instead of choosing tools by hype or generic benchmarks. Languages: Markdown, spreadsheets, research notes, AI-assisted analysis workflows. Access: private/internal research; public profile contains only a sanitized project summary. Highlight: model and tool comparison, enterprise risk assessment, data-handling constraints, cost and licensing review, employee workflow mapping, governance criteria, and recommendation-ready documentation. |
|
🏅 4. Volatility Framework
Python framework for cleaner volatility analysis workflows and reusable quantitative experiments. Open detailsGoal: make volatility analysis workflows more reusable and easier to experiment with. Languages: Python. Access: public repository. Highlight: reusable quantitative tooling and personal framework design. |
Research notebook workspace for thesis experiments, calculations, and structured analysis. Open detailsGoal: organize thesis research, experiments, calculations, and analysis notebooks. Languages: Jupyter Notebook, Python. Access: private repository; visible only to approved collaborators. Highlight: research workflow, notebook-based analysis, and academic project structure. |
🏅 6. WebTech Projects
Full WebTech collection with a PHP database site, REST API extension, and real-time WebSocket game. Open detailsGoal: present a three-part web development sequence: database-backed PHP app, protected REST API, and browser multiplayer game. Languages: PHP, JavaScript, HTML, CSS, SQL. Access: public repository. Highlight: authentication, Google OAuth, 2FA, MariaDB schema work, JWT API flows, and WebSocket real-time gameplay. |
Polished AI lab portfolio with graph search, propositional logic resolution, ID3 decision trees, and a neural network trained with a genetic algorithm. Open detailsGoal: present core AI and machine learning lab work as a clean, runnable GitHub portfolio project. Languages: Python, CSV examples, Markdown documentation. Access: public repository. Highlight: four documented labs, example inputs, runnable commands, and sanitized archive cleanup. |
|
AI-assisted testing case study for a Java/JPA assignment with runnable Codex-generated JUnit tests and model comparison notes. Open detailsGoal: turn a one-prompt AI testing task into a clean Maven project with documented generated outputs. Languages: Java, JUnit 4, JPA, Maven, Markdown. Access: public repository. Highlight: runnable tests, `BODY = 10` verification, Codex/Gemini/ChatGPT comparison, and sanitized submission artifacts. |
🏅 9. Nomad System Design
Sanitized system-analysis case study for a car-rental platform with UML diagrams, acceptance tests, and project planning artifacts. Open detailsGoal: present requirements analysis and UML documentation for a realistic car-rental management system. Languages: Markdown, UML, PDF documentation. Access: public repository. Highlight: use-case, class, activity, sequence, state, acceptance-test, Gantt, and network diagrams in a portfolio-safe format. |
🏅 10. Bogatyr Game
Browser game project for interactive JavaScript gameplay experiments. Open detailsGoal: build and experiment with browser-based interactive gameplay. Languages: JavaScript, HTML, CSS. Access: private repository; visible only to approved collaborators. Highlight: front-end interaction, game logic, and creative coding. |
🏅 11. KUIT IT Instruction
Instruction-style HTML project for presenting IT learning material in a simple web format. Open detailsGoal: present IT instruction content in a simple static web page format. Languages: HTML, CSS. Access: public repository. Highlight: clean instructional content and lightweight page structure. |
