B.Tech CSE (2022–2026) | I build clean, reliable web apps and APIs with strong fundamentals and real project work — currently seeking internships and jobs.
Download CVHi, I'm Syed Ishaq from Andhra Pradesh, India — a 2026 CSE graduate. I'm interested in building software that feels clear and dependable: simple interfaces, clean logic, and systems that don't fall apart when real users show up. I learn fastest by building, then tightening what I built — cleaner structure, fewer bugs, faster flows, and clearer results. This site is written to be quick to skim on purpose, because people don't read pages line-by-line; they scan for signal.
Read MoreTechnologies and tools I work with on a daily basis
C
Java
Python
MySQL
HTML5
CSS3
JavaScript
Bootstrap
React
Node.js
Express
Django
Fast API
MongoDB
NumPy
Scikit-learn
Pandas
matplotlib
NLTK
AWS
Salesforce
ServiceNow
Power BI
MS Excel
Jupyter
VS Code
GitAug 2022 — Apr 2026
Bachelor of Technology — Computer Science
Jul 2020 — May 2022
Intermediate — MPC
Mar 2020
Secondary School Certificate
Check out some of my personal and paid projects
Built a full-stack Learning Management & Assessment platform (React + Vite + TailwindCSS frontend, Node.js/Express + MongoDB backend) featuring OTP email verification, JWT auth with refresh tokens, role-based access (admin/user), quiz & coding assessments, assignment management, submission review, dashboards, and monthly reporting — deployed on GitHub Pages + Vercel.
Built a MERN-based food ordering app (user + admin panels) with JWT authentication, cart + order management, and Stripe payment integration.
Built an AI-powered support desk using Node/Express + MongoDB + React with Inngest to run ticket triage asynchronously via Google Gemini, enabling auto priority/tag extraction, skill-based moderator routing (RBAC), and email notifications, while reducing API latency ~60%.
Built a full-stack stock analytics dashboard using React and Django REST Framework, featuring JWT authentication, real-time stock charts, watchlist management, and ML-based price forecasting (Linear Regression/LSTM) via API-driven predictions.
Built an end-to-end analytics pipeline on 3,900+ retail records: performed Python ETL + feature engineering, wrote advanced SQL (CTEs, window functions) for segmentation and revenue insights, and delivered an interactive Power BI dashboard with DAX KPIs to evaluate subscription ROI, shipping impact, and discount efficiency.
A full-stack web app (React SPA + FastAPI) that classifies news text as Reliable or Unreliable in real time using an NLP/ML pipeline (TF-IDF uni+bi-grams + Logistic Regression).