Javascript is a language

PHP programming language

CSS covers styling and layout in frontend development—how a website looks and adapts. It includes selectors and the cascade, box model, positioning and Flexbox/Grid, typography and colors, responsive design (media/container queries), animations/transitions, and building reusable UI themes and components.

Develop and maintain iOS mobile applications using UIKit and SwiftUI · Design and implement new features, optimize and refactor existing code

Tests for Python Development path

Soft skills

Frontend System Design is a hard skill—it’s about technical architecture. But it’s evaluated alongside soft skills (communication & trade-off reasoning). App architecture & state strategy (SPA/MPA, SSR/ISR, microfrontends) Performance budgets, caching, CDN/edge, code-splitting API contracts, schema/versioning, error handling & resiliency Design system architecture, accessibility, i18n Testing strategy, observability, security, and deployments

SQL Databases questions evaluate a candidate’s understanding of relational data, querying, joins, indexing, normalization, transactions, and performance optimization. These questions help assess how well a developer can design database structures, write efficient queries, and work with real-world data reliably.

Category focused on command-line skills, shell scripting, and everyday terminal usage for developers. It covers working with files, processes, permissions, pipes, redirection, and common Unix-like system commands used in real development and DevOps workflows.

Application security for developers building React frontends and Node.js backends. Covers secure design, authentication and authorization, browser and API defenses, input validation, data protection, dependency and container security, logging, and production safeguards across the full-stack development lifecycle.

Database optimization interview questions focused on query performance, indexing, execution plans, joins, pagination, transactions, and practical strategies for improving database efficiency in real-world systems.

MongoDB Performance Tuning category focused on improving query speed, indexing efficiency, schema design, aggregation performance, and scaling strategies for real-world MongoDB applications.

Embedded Development covers the design and programming of software that runs directly on hardware devices. This category includes microcontrollers, real-time systems, sensors, communication protocols, memory management, hardware interfaces, debugging, and performance optimization for resource-constrained environments.

Electronics Basics covers foundational electronics knowledge for embedded engineers, including circuit fundamentals, basic components, schematic reading, practical signal handling, and power and protection concepts.

Master C and C++ for embedded systems, including memory management, pointers, bitwise operations, hardware register access, interrupt-safe code, real-time constraints, and efficient interaction with microcontrollers and peripherals.

Assesses practical knowledge of Docker fundamentals, including images, containers, Dockerfiles, volumes, networking, registries, Docker Compose, security, troubleshooting, and container lifecycle management. Covers the ability to containerize applications, configure reproducible environments, optimize builds, manage persistent data and service communication, diagnose common runtime issues, and apply reliable containerization practices in development and production.

This category assesses practical PCB design knowledge, from schematic capture and component selection to board layout, placement, routing, and manufacturing preparation. It covers footprints, PCB stackups, power and ground design, signal integrity, EMI/EMC, thermal considerations, design-rule verification, DFM, board bring-up, and hardware debugging. Questions evaluate the ability to create reliable, manufacturable, and maintainable printed circuit boards while balancing electrical, mechanical, thermal, and cost constraints

Learn how to design, build, evaluate, and operate production-ready AI applications. Explore large language models, prompt engineering, embeddings, vector databases, RAG, AI agents, model evaluation, observability, security, cost optimization, and reliable deployment practices.