DSA Questions
Practice hand-picked problems organized by pattern — from arrays and trees to dynamic programming and graphs.
- ✓Arrays & Strings
- ✓Linked Lists & Trees
- ✓Graphs & BFS/DFS
- ✓Dynamic Programming & Greedy
Master Tech Stacks.
Build Real Clarity.
Learn Frontend , Backend and System Design through structured roadmaps, deep explanations and Interview-focused learning
- Beginner to Advanced structured roadmaps
- Real-world examples & mental models
- Interview-focused learning paths
Interview Preparation
Structured resources to help you crack top tech interviews — covering DSA patterns, system design fundamentals, and real-world coding challenges.
System Design
Learn to design scalable, reliable systems — from high-level architecture to database and API choices.
- ✓Scalability & Load Balancing
- ✓Databases & Caching
- ✓Microservices & APIs
- ✓Real-world Case Studies
Machine Coding Round
Build real-world mini-projects under time constraints — clean code, solid design patterns, and working output.
- ✓OOP & Design Patterns
- ✓Component Architecture
- ✓State Management
- ✓Time-boxed Problem Solving
Learning Stacks
Structured learning paths that guide you step by step, helping you build practical skills used in real projects and jobs.
Frontend - (Website Development)
View RoadmapJavaScript
Bring websites to life.
- ✓Core JavaScript concepts
- ✓DOM manipulation
- ✓Async programming
- ✓Writing clean, readable code
React
Build scalable user interfaces.
- ✓Component thinking
- ✓State & props
- ✓Hooks & rendering flow
- ✓Building real projects
Redux
Manage and scale application state.
- ✓Redux concepts and architecture
- ✓State management patterns
- ✓store, actions, reducers
- ✓Debugging and optimizing state flow
Next Js
Build fast, SEO-friendly
- ✓Server-Side Rendering (SSR)
- ✓Static Site Generation (SSG)
- ✓Client and Server Components (App Router)
- ✓SEO optimization and metadata handling
Web Fundamentals
how web and browsers actually work.
- ✓How the web works
- ✓Cookies, LocalStorage, and SessionStorage
- ✓HTTP basics, status codes, and headers
- ✓Same-origin policy and CORS fundamentals
Website Performance
Build fast, scalable, and high-performing.
- ✓web performance (LCP, FCP, CLS, TTI)
- ✓Optimizing asset loading
- ✓Code splitting and lazy loading strategies
- ✓Improving rendering performance and reflows
Frontend System Design
Design scalable and production-ready
- ✓Designing large-scale frontend applications
- ✓right state management approach
- ✓Performance and scalability considerations
- ✓Code splitting and module organization
Frontend - (Mobile App Development)
View RoadmapReact Native
Build cross-platform mobile apps.
- ✓React Native components & layout system
- ✓Styling with Flexbox
- ✓Navigation and screen management
- ✓Building real-world mobile apps
Backend
View Roadmapjava
Core Java programming and backend fundamentals.
- ✓Core Java & OOP principles
- ✓Collections & generics
- ✓Concurrency & multithreading
- ✓JVM tooling and debugging
springboot
Build production-ready Java backend services with Spring Boot.
- ✓Spring Boot fundamentals & starters
- ✓REST API design with Spring MVC
- ✓Spring Data JPA & database integration
- ✓Security, testing, and deployment
Databases
Design, query and scale databases for production.
- ✓Relational schema design
- ✓Indexing & query optimization
- ✓Transactions & ACID
- ✓Replication & scaling patterns
Node.js
Build scalable backend services with JavaScript.
- ✓Node runtime & async patterns
- ✓Express and middleware
- ✓REST API design & authentication
- ✓Testing and deployment
APIs
Connect applications seamlessly.
- ✓RESTful API design
- ✓Authentication & security
- ✓Error handling
- ✓API documentation
AI & Machine Learning
View RoadmapPython Fundamentals
The language for AI and ML development.
- ✓Python syntax and data structures
- ✓Libraries: NumPy, Pandas, Scikit-learn
- ✓Data manipulation and analysis
- ✓Writing efficient and clean code
Machine Learning Basics
Build intelligent systems from data.
- ✓ML fundamentals and algorithms
- ✓Supervised vs unsupervised learning
- ✓Feature engineering and preprocessing
- ✓Model training and evaluation
Deep Learning
Harness neural networks for complex tasks.
- ✓Neural networks and backpropagation
- ✓TensorFlow and PyTorch frameworks
- ✓CNNs for image processing
- ✓RNNs and Transformers for sequence learning
Natural Language Processing
Teach computers to understand language.
- ✓Text preprocessing and tokenization
- ✓Word embeddings and representations
- ✓Building NLP models with transformers
- ✓Sentiment analysis and text classification
Large Language Models (LLMs)
Work with state-of-the-art AI models.
- ✓Understanding LLM architectures
- ✓Prompt engineering best practices
- ✓Fine-tuning and transfer learning
- ✓Integrating LLMs into applications
AI/ML Project Development
Deploy AI models in production.
- ✓Project structure and best practices
- ✓Data collection and preprocessing pipelines
- ✓Model deployment and serving
- ✓Monitoring and maintaining ML systems