This article is written for computer science engineering (CSE) students who want practical, grade-worthy projects that teach important concepts and look good on resumes.
Below you’ll find a clear introduction, tips for choosing a project, and 50 well-explained project ideas.
Each project includes: a short description, suggested technologies/tools, main features to implement, difficulty level, and a brief example or implementation note. You can copy-paste any section directly.
Introduction
As a CSE student, building projects is the fastest way to turn theory into real skills. Projects help you understand algorithms, data structures, system design, networking, databases, security, and full-stack development. Good projects also show recruiters that you can plan, implement, test, and present a working solution.
This article lists 50 engineering project ideas for CSE across different domains: web, mobile, AI/ML, systems, networking, security, databases, and DevOps. Each idea is practical, scalable, and adaptable — you can keep the core scope for a semester or extend it into a bigger capstone. For each idea, I provide technologies, features, difficulty, and an example implementation approach so you can get started immediately.
Also Read: 99+ Famous Profile Sekai Project Ideas For Students
How to choose the right project
- Match your course requirements. If your program requires a report, choose a project with measurable experiments.
- Balance scope and time. Start small: a minimum viable product (MVP) first, then add features.
- Focus on learning outcomes. Pick projects that teach skills you want (e.g., ML, system design, security).
- Reuse libraries and APIs. Use existing tools (frameworks, pre-trained models) to save time.
- Document everything. Write a plan, architecture diagram, test cases, and usage instructions.
50 Engineering Project Ideas for CSE 2026
1. Student Management System (Web)
Description: A full-stack web application to manage student data — registration, attendance, grades, reports.
Technologies: React or Angular, Node.js/Express, MongoDB/Postgres, JWT authentication.
Main features: CRUD for students/courses, role-based access (admin/teacher/student), attendance tracker, gradebook, CSV import/export.
Difficulty: Beginner → Intermediate.
Example: Implement attendance marking with date-wise records and generate PDF mark sheets.
2. Online Examination Portal
Description: A secure online test platform with timed exams and automated evaluation.
Technologies: Django/Flask or Spring Boot, Vue/React, PostgreSQL, WebSocket for live timer.
Main features: Question bank, multiple question types, proctoring options (basic), timer, auto-grading and analytics.
Difficulty: Intermediate.
Example: Add an algorithm to randomize question order and prevent reattempts after submission.
3. E-commerce Website (Minimal)
Description: A shopping website with product catalog, cart, orders, and payments (sandbox).
Technologies: MERN stack (MongoDB, Express, React, Node), Stripe/PayPal sandbox.
Main features: Product listing, search and filter, shopping cart, checkout, order history, admin dashboard.
Difficulty: Intermediate.
Example: Implement search autocomplete and a recommendation based on user history.
4. Chat Application with Real-time Messaging
Description: A real-time chat app supporting one-to-one and group chats.
Technologies: Socket.IO with Node.js, React Native for mobile or React for web, Redis for pub/sub.
Main features: Message persistence, typing indicators, read receipts, media sharing.
Difficulty: Intermediate.
Example: Implement offline message sync and message delivery acknowledgment.
5. Library Management System (Desktop/Web)
Description: Manage book catalog, issue/return, fines, and inventory.
Technologies: JavaFX or .NET for desktop, or web stack with Django and PostgreSQL.
Main features: Barcode scanning, book reservation, member management, reporting.
Difficulty: Beginner → Intermediate.
Example: Auto-calculate late fees and email reminders for due dates.
6. Personal Finance Tracker
Description: Help users track income, expenses, budgets, and create visual reports.
Technologies: React Native or Flutter, Firebase or SQLite, Chart.js or D3.js.
Main features: Transaction categories, budget alerts, monthly graphs, CSV export.
Difficulty: Beginner.
Example: Add a predictive monthly expense estimator using moving averages.
7. Traffic Sign Recognition (Computer Vision)
Description: Detect and classify traffic signs from images/video (useful for autonomous vehicles).
Technologies: Python, OpenCV, TensorFlow/Keras, pre-trained CNN models (transfer learning).
Main features: Image preprocessing, model training, real-time detection with webcam feed.
Difficulty: Intermediate → Advanced.
Example: Fine-tune a MobileNet model on a traffic sign dataset and run live detection.
8. Handwritten Digit Recognition (ML)
Description: Classic MNIST classification problem extended with a GUI.
Technologies: Python, TensorFlow/PyTorch, Flask for web UI or Tkinter for desktop.
Main features: Training pipeline, accuracy visualization, live digit drawing and prediction.
Difficulty: Beginner.
Example: Build a web interface where users draw a digit and the model predicts the number.
9. Gesture-controlled Media Player
Description: Control playback (play/pause/next) with hand gestures via webcam.
Technologies: OpenCV, MediaPlayer libs, pretrained hand keypoint detectors (MediaPipe).
Main features: Gesture recognition, mapping gestures to controls, calibration screen.
Difficulty: Intermediate.
Example: Use MediaPipe to detect open/closed palm and toggle play/pause.
10. Social Media Sentiment Analyzer
Description: Analyze sentiments of tweets or posts about a topic and present analytics.
Technologies: Python, Tweepy (or social API), NLTK/spaCy, scikit-learn or transformers, Dash/Streamlit.
Main features: Data collection, sentiment classification, trending topics, charts.
Difficulty: Intermediate.
Example: Collect tweets about a new phone and show sentiment over time with word clouds.
11. URL Shortener with Analytics
Description: A service that shortens URLs and tracks click stats and sources.
Technologies: Node.js/Express, Redis for caching, MongoDB/Postgres, Nginx.
Main features: URL creation, redirection, click counters, location/time analytics, custom aliases.
Difficulty: Beginner → Intermediate.
Example: Provide an admin page showing top referrers and device types.
12. Plagiarism Detection System
Description: Compare documents for similarity using text preprocessing and algorithms.
Technologies: Python, TF-IDF, cosine similarity, shingling (n-gram), Flask/React for UI.
Main features: File upload, similarity percentage, highlighted matching passages, report generation.
Difficulty: Intermediate.
Example: Use 3-gram shingles and compute cosine similarity between documents.
13. IoT-based Smart Home Controller
Description: Control lights, fans, and sensors via a web/mobile app connecting to IoT devices.
Technologies: Raspberry Pi/Arduino, MQTT, Firebase/Node-RED, React Native.
Main features: Device discovery, scheduling, sensor data charts (temperature/humidity).
Difficulty: Intermediate → Advanced.
Example: Use MQTT broker to toggle a relay connected to a Raspberry Pi GPIO pin.
14. Resume Builder with Templates
Description: An online resume builder with multiple templates, PDF export, and tips.
Technologies: React, Node.js, jsPDF or Puppeteer for PDF generation, MongoDB for storage.
Main features: Template selection, drag-and-drop sections, export to PDF, profile sharing link.
Difficulty: Beginner.
Example: Implement live preview of the resume and export as a downloadable PDF.
15. Expense Splitter App (Group Expense)
Description: Split bills among friends, track balances, and simplify settlements.
Technologies: Flutter for cross-platform mobile, Firebase Auth and Firestore.
Main features: Create groups, add expenses, balances per person, push notifications.
Difficulty: Beginner → Intermediate.
Example: Show net owing for each member and propose minimal transactions to settle debts.
16. Image Caption Generator
Description: Generate natural-language captions for images using encoder-decoder models.
Technologies: Python, TensorFlow/Keras, CNN (encoder) + LSTM/Transformer (decoder).
Main features: Image preprocessing, beam search for caption generation, evaluation metrics (BLEU).
Difficulty: Advanced.
Example: Use InceptionV3 as encoder and an LSTM decoder trained on MS-COCO subset.
17. Smart Parking System
Description: Manage parking slots in real time, showing available slots and automatic billing.
Technologies: IoT sensors or camera-based detection (OpenCV), Node.js, PostgreSQL.
Main features: Slot occupancy detection, reservation, payment integration, admin analytics.
Difficulty: Intermediate → Advanced.
Example: Use ultrasonic sensors to detect slot occupancy and update a web dashboard.
18. E-Learning Platform with Quiz Builder
Description: A platform for creating and taking courses with integrated quizzes and progress tracking.
Technologies: Laravel or Django, React, PostgreSQL, AWS S3 for content.
Main features: Course authoring, video lectures, quizzes with auto-grading, progress analytics.
Difficulty: Intermediate.
Example: Implement adaptive quizzes that change difficulty based on past performance.
19. Voice Assistant (Basic)
Description: Build a voice assistant that can answer simple queries and perform system tasks.
Technologies: Python, SpeechRecognition library, pyttsx3 for TTS, APIs for weather/news.
Main features: Wake word, voice commands, simple task execution (open apps, search web).
Difficulty: Intermediate.
Example: Recognize “open notepad” and execute a system call to open an application.
20. URL/Classified Ads Scraper with Dashboard
Description: Scrape classified websites for certain items and show aggregated results.
Technologies: Python, BeautifulSoup/Scrapy, PostgreSQL, Dash or Flask for dashboard.
Main features: Scheduler for scraping, deduplication, price trend graphs, alerts for matches.
Difficulty: Intermediate.
Example: Scrape listings for used laptops and alert when price < threshold.
21. Online Food Ordering System (with Delivery Tracking)
Description: Customers order food, restaurants update status, and delivery is tracked in real time.
Technologies: React Native (mobile), Node.js backend, MongoDB, Google Maps API for tracking.
Main features: Menu management, order lifecycle updates, delivery routing, ratings.
Difficulty: Intermediate.
Example: Show driver location on map and compute ETA using directions API.
22. Blockchain-based Voting System
Description: Secure voting using blockchain for immutable, verifiable records.
Technologies: Ethereum (Solidity), Web3.js, React, Ganache for testing.
Main features: Voter registration, secure ballot casting, immutable ledger, results verification.
Difficulty: Advanced.
Example: Implement smart contracts to store votes and provide a front-end to read events.
23. Fitness Tracker with Workout Plans
Description: Track workouts, calories, and suggest plans based on goals.
Technologies: Flutter or React Native, SQLite or Firebase, charts for progress.
Main features: Workout logging, personalized plans, progress charts, reminders.
Difficulty: Beginner.
Example: Recommend a 4-week strength plan based on user input (beginner/intermediate).
24. Real-time Stock Market Dashboard
Description: Live visualization of stock prices, portfolio tracking, and alerts.
Technologies: React, WebSocket for live data, APIs for stock data, D3/Chart.js for graphs.
Main features: Watchlists, historical charts, technical indicators, price alerts.
Difficulty: Intermediate.
Example: Show moving average crossover signals and notify users about events.
25. Secure File Storage with Encryption
Description: Cloud-like file storage that encrypts files on client side before upload.
Technologies: Node.js, AWS S3 or Firebase Storage, crypto libraries (AES/RSA).
Main features: Client-side encryption, secure key management, shareable encrypted links.
Difficulty: Advanced.
Example: Use RSA to encrypt AES keys and AES for file encryption; store encrypted keys on server.
26. Recommendation System for Movies
Description: Build content-based and collaborative filtering recommendation engine.
Technologies: Python, scikit-learn, Surprise library, Flask for API, React dashboard.
Main features: User-based and item-based recommendations, hybrid approach, test metrics.
Difficulty: Intermediate → Advanced.
Example: Train on MovieLens dataset and serve top-N recommendations for a user.
27. Optical Character Recognition (OCR) System
Description: Convert images of documents into editable text; support multiple languages.
Technologies: Python, Tesseract OCR, OpenCV for preprocessing, Flask + React UI.
Main features: Image enhancement, text extraction, downloadable text/PDF.
Difficulty: Intermediate.
Example: Preprocess scanned images with thresholding to improve OCR accuracy.
28. Attendance Using Face Recognition
Description: Automatic attendance system that recognizes faces and logs presence.
Technologies: Python, OpenCV, face_recognition library (dlib), SQLite.
Main features: Enroll students, real-time recognition, logs, export attendance sheets.
Difficulty: Intermediate.
Example: Use HOG or CNN-based face encodings to match classroom faces.
29. Malware Analysis Sandbox (Educational)
Description: Safe environment to run and analyze suspicious files (with strict safety).
Technologies: Virtual machines (VirtualBox), Python, Cuckoo Sandbox concepts, logging and analysis.
Main features: File upload (offline), behavior monitoring, network capture (isolated), report builder.
Difficulty: Advanced (security concerns).
Example: Create a VM snapshot, run sample in VM, collect process and network logs for analysis.
Note: Implement with caution and do not run real malware on public or home networks.
30. Voice-to-Text Meeting Summarizer
Description: Transcribe meeting audio and generate concise summaries.
Technologies: Speech-to-text APIs (or open-source models), Python, NLP summarization models (transformers).
Main features: Speaker diarization, transcript export, key-point summary, search within transcripts.
Difficulty: Advanced.
Example: Record meeting, transcribe, then run an abstractive summarizer to create minutes.
31. Online Grocery Store with Inventory Forecasting
Description: E-commerce for groceries with demand forecasting for inventory.
Technologies: MERN stack, basic ML (ARIMA/Prophet), PostgreSQL, Redis cache.
Main features: Product listing, order management, stock prediction, low-stock alerts.
Difficulty: Intermediate → Advanced.
Example: Forecast next month’s demand for a product and automatically suggest reorder quantities.
32. Password Manager (Local/Cloud)
Description: Securely store and retrieve user passwords with encryption and master password.
Technologies: Electron for desktop app or Flutter mobile, AES encryption, hashed master password.
Main features: Add/edit passwords, password generator, auto-lock after idle, backup/export encrypted.
Difficulty: Intermediate.
Example: Generate site-specific strong passwords and store them encrypted on disk.
33. News Aggregator with Topic Clustering
Description: Aggregate news from multiple sources and cluster similar stories into topics.
Technologies: Python, RSS/News APIs, TF-IDF embeddings or transformers, clustering algorithms.
Main features: Source aggregation, topic clusters, summarization, search.
Difficulty: Intermediate.
Example: Cluster articles about a single event from different outlets and show unified timeline.
34. Bug Tracker / Issue Management System
Description: Tool for managing project issues, sprints, and bug reports.
Technologies: Django or Rails, React frontend, PostgreSQL, JWT.
Main features: Issue creation, tagging, status workflow, assignees, comments, reporting.
Difficulty: Beginner → Intermediate.
Example: Add a Kanban board UI and auto-notify assignees on status change.
35. Data Visualization Dashboard for Open Data
Description: Visualize government or public datasets and allow interactive exploration.
Technologies: Python (Pandas), Flask, D3.js/Chart.js, PostgreSQL.
Main features: Dataset importer, filtering, interactive charts, download options.
Difficulty: Intermediate.
Example: Visualize population vs literacy rate across regions with heatmaps and line charts.
36. Auction Website (Real-time Bidding)
Description: Platform for timed auctions with real-time bidding and winner determination.
Technologies: Node.js, WebSockets, React, PostgreSQL, payment gateway integration.
Main features: Live bid updates, auto-bid, auction timers, seller dashboards.
Difficulty: Intermediate → Advanced.
Example: Implement highest-bid-wins logic and anti-sniping (extend auction if last-second bid).
37. QR Code-based Event Check-in System
Description: Generate QR codes for attendees and scan them at entry for quick check-in.
Technologies: React Native for scanner app, Node.js backend, QR code libraries.
Main features: Ticket generation, QR scanning, attendance logs, check-in reports.
Difficulty: Beginner.
Example: Generate unique encrypted token in QR code and validate on scan with server verification.
38. Task Automation Bot (Web Scraping + Actions)
Description: A bot that automates routine web tasks, like data entry or form submissions.
Technologies: Python, Selenium/Playwright, scheduling with Celery or cron.
Main features: Scriptable tasks, retry logic, error reporting, credential management.
Difficulty: Intermediate.
Example: Automate daily login and report download from an intranet site (with permission).
39. Multi-tenant SaaS Boilerplate
Description: Skeleton application supporting multiple organizations (tenants) with isolated data.
Technologies: Django/Flask with SQLAlchemy, PostgreSQL schemas, React frontend.
Main features: Tenant onboarding, role-based access, billing placeholder, single codebase multi-tenant support.
Difficulty: Advanced.
Example: Implement schema-based isolation and admin-level tenant management.
40. CAPTCHA Solver (Research Project)
Description: Analyze and attempt to solve CAPTCHA variants; focus on limitations and defenses.
Technologies: Python, OpenCV, ML models for OCR, ethical use and research-only controls.
Main features: Preprocessing pipeline, classifier, report on success rates, recommendations to strengthen CAPTCHAs.
Difficulty: Advanced.
Example: Use image segmentation then feed to an OCR model; document ethical implications and defensive suggestions.
Note: Use only for research; do not use to bypass protections illegally.
41. Medical Diagnostic Assistant (Symptom Checker)
Description: System that suggests possible conditions from symptoms using rule-based and ML approaches.
Technologies: Python, knowledge base (medical datasets), NLP for symptom parsing, web UI.
Main features: Symptom input, probable diagnoses with confidence scores, triage advice.
Difficulty: Advanced.
Example: Combine decision trees for common conditions and ML model for rare pattern detection; include disclaimers.
42. Real-time Collaborative Editor
Description: A Google Docs-like collaborative text editor with operational transformation or CRDT.
Technologies: Node.js, WebSocket, operational transformation (OT) libraries or CRDT implementations, React.
Main features: Real-time cursor position of collaborators, conflict resolution, version history.
Difficulty: Advanced.
Example: Use Yjs (CRDT) or ShareDB (OT) to handle concurrent edits and sync clients.
43. Sentiment-based Music Playlist Generator
Description: Generate playlists matching the user’s mood from streaming metadata.
Technologies: Python, Spotify API, sentiment analysis on user input or recent texts.
Main features: Mood detection, song feature matching (tempo, valence), playlist creation.
Difficulty: Intermediate.
Example: Detect user mood as “energetic” and create a playlist emphasizing high-tempo tracks.
44. Dynamic Quiz Generator with Adaptive Difficulty
Description: Generates quizzes that adapt question difficulty based on user performance.
Technologies: Django or Node.js, React, a small ML model or heuristic for adaptation.
Main features: Question bank tagging by difficulty, adaptive selection, performance analytics.
Difficulty: Intermediate.
Example: If a student answers three consecutive questions correctly, increase difficulty level.
45. CAPTCHA Generator (Security Study)
Description: Create robust CAPTCHAs exploring trade-offs between usability and security.
Technologies: Python, image libraries, audio CAPTCHA support, accessibility options.
Main features: Image/text/audio CAPTCHAs, distortion algorithms, rate limiting.
Difficulty: Intermediate → Advanced.
Example: Generate image CAPTCHAs using stylized fonts and background noise; test solvability.
46. Smart To-Do App with NLP Input
Description: Take natural language input (“tomorrow 9 AM meeting”) and add structured tasks with reminders.
Technologies: Flutter/React Native, NLU (spaCy/transformers), local notifications.
Main features: Natural language parsing to extract date/time/tags, recurring tasks, priority sorting.
Difficulty: Intermediate.
Example: Parse “Pay electricity bill every month” and create a recurring task with monthly reminders.
47. Containerized Microservices Demo
Description: Build a sample microservices application with multiple services and orchestrate them with Docker Compose/Kubernetes.
Technologies: Docker, Kubernetes (minikube), REST/gRPC, Redis, PostgreSQL.
Main features: Service discovery, health checks, load balancing, CI/CD pipeline example.
Difficulty: Advanced.
Example: Split an e-commerce app into catalog, orders, and user services and deploy with minikube.
48. CAPTCHA-resistant Login System
Description: Design login flows minimizing bot access using rate limiting, device fingerprinting, and progressive challenges.
Technologies: Node.js, Redis, fingerprintJS, reCAPTCHA integration options.
Main features: Brute-force protection, progressive challenge escalation, audit logs.
Difficulty: Advanced.
Example: Lockout policies combined with incremental challenge difficulty for suspicious IPs.
49. Language Learning App with Spaced Repetition
Description: Mobile/web app that schedules vocabulary reviews using spaced repetition algorithms (SRS).
Technologies: React Native or Flutter, local storage or Firebase, SM-2 algorithm implementation.
Main features: Flashcards, SRS scheduling, progress statistics, audio pronunciation.
Difficulty: Intermediate.
Example: Implement SM-2 to schedule next review based on user recall rating.
50. Automated Code Grading Platform
Description: A platform that runs student code against test cases with sandboxing and reports results.
Technologies: Docker sandboxing, Node.js/Python backend, language runners, database for submissions.
Main features: Support multiple languages, test case management, plagiarism checks, leaderboard.
Difficulty: Advanced.
Example: Use Docker containers to compile/run code safely and compare outputs with expected results.
Must Read: 150 8D Project Ideas 2025-26
Tips to implement these projects successfully
- Start with an MVP: Implement core functionality first (e.g., login + main feature), then extend.
- Version control: Use Git and push frequently with clear commits.
- Testing: Add unit tests and integration tests for key modules.
- Documentation: Maintain README, installation steps, and usage examples—important for grading interviews.
- UI/UX: Even a simple, clean interface elevates presentation.
- Deployment: Deploy on Heroku, Vercel, Netlify, or a VPS to show live demos.
- Security & Privacy: Handle user data responsibly—hash passwords and validate input to avoid vulnerabilities.
- Use templates & libraries: Don’t reinvent the wheel—use established libraries (Bootstrap/Tailwind, Auth libraries).
- Time management: Allocate weeks for planning, implementation, testing, and documentation.
Conclusion
These 50 engineering project ideas for CSE span beginner to advanced levels and cover web/mobile development, machine learning, computer vision, IoT, blockchain, security, and system design.
Choose a project that aligns with your learning goals and available time.
Start with a clear plan, implement an MVP, and iterate.
Good documentation and a hosted demo significantly increase the impact of your project when applying for internships or showcasing in your portfolio.
