A CV review is when an experienced professional evaluates your CV for structure, relevance, clarity, and impact — checking whether it passes applicant tracking systems (ATS), whether achievements are quantified, and whether it matches the roles you're targeting. In India, CV and resume are used interchangeably, so a CV review and a resume review are effectively the same thing. You need one most when applying to product-based companies, switching after several years at one organisation, or not getting interview calls despite applying regularly.

Start by matching it against the specific job description — skills, keywords, and your title should mirror what the role asks for. Make sure every bullet point follows a "did X, achieved Y" pattern with numbers wherever possible, keep the layout clean and ATS-friendly (avoid graphics-heavy templates), and read it aloud to catch awkward phrasing and typos. Finally, get one outsider's opinion, because self-review almost always misses how a hiring manager perceives your profile in the first 30 seconds.

Paste your resume along with the exact job description and review one aspect at a time — keyword alignment, weak verbs, missing metrics, and ATS readability — instead of asking for everything at once. A simple resume review prompt to start with: "Act as an experienced technical recruiter. Review this resume against the job description below, list every reason it could get rejected, and suggest specific rewrites for weak bullets." Remember that AI feedback is generic, so treat it as a useful first filter rather than a final verdict.

A free resume review — through AI tools, friends, or online communities — is usually enough to fix formatting, grammar, and obvious structural issues. What free options rarely catch is positioning: whether your projects are framed the way product companies expect, whether your impact reads at the right level, and why recruiters might be filtering you out. If you're repeatedly rejected without calls, targeting a big switch, or returning after a gap, a paid resume review service from someone who has worked in those companies typically pays for itself.

The mock interview meaning is simple: it is a simulated practice interview that replicates the format, questions, and pressure of a real one, followed by honest feedback on your answers and communication. Mocks are used for technical rounds, HR rounds, and panel interviews alike. The biggest benefit is failing in a low-stakes setting — you discover rambling answers, weak explanations, and nerves during practice instead of in front of the actual interviewer, and one corrective mock is often worth days of silent revision.

Share the job description and your resume with an AI chatbot, ask it to interview you one question at a time covering technical, situational, and HR rounds, and instruct it not to reveal answers until you've attempted each one. Follow up by asking it to grade your responses on structure, clarity, and depth, then repeat the weak areas. AI mocks are excellent for building fluency and answering out loud, but they can't recreate real pressure, probing follow-ups, or interviewer intuition — so pair them with human mocks closer to the interview.

Popular options include peer-to-peer mock platforms, interview-prep communities on Reddit and Discord where candidates exchange mocks, AI tools that simulate interviews, and alumni or placement networks if you're a student. The catch with free mock interview practice online is inconsistent quality — partners cancel often, and feedback tends to be polite rather than honest. If you're preparing for a specific company or a seniority jump, practising with someone who has actually interviewed at that company or level gives far more realistic feedback.

A good mock interview for freshers should cover four things: a crisp self-introduction with common HR questions, basic technical or core-subject questions drawn from your resume, easy-to-moderate DSA problems solved while thinking aloud, and communication under time pressure. Since freshers are judged mainly on fundamentals, clarity of thought, and trainability rather than deep experience, the feedback should focus on structuring answers and avoiding memorised-sounding responses. One or two honest mocks typically fix more than weeks of solo preparation.

Don't just read answers — attempt every question out loud first, then compare it with a model answer, because the gap between what you know and what you can articulate under pressure is where most candidates lose out. Use the STAR format for behavioural questions, time your DSA practice like a real round, maintain a document of every question you fumbled, and revisit it weekly. Once individual answers feel solid, string them together into a full-length mock, since interviews test stamina and consistency, not just isolated knowledge.

The most asked frontend interview questions cluster around JavaScript fundamentals — closures, the event loop, promises and async behaviour, debouncing, and prototypes — along with framework questions on React or your primary library, such as hooks, the virtual DOM, and state management. Expect CSS layout tasks, browser and performance topics like caching, lazy loading, and Core Web Vitals, plus one or two easy-to-medium DSA problems. Many product companies also include a live machine-coding round where you build something like an autocomplete, todo app, or infinite scroll.

As a fresher, the bar is fundamentals over depth: semantic HTML, CSS positioning and flexbox vs grid, JavaScript basics like var-let-const, hoisting, and array or string methods, and simple framework questions if the role demands it. Frontend interview questions for freshers usually include easy-level DSA, and interviewers spend significant time digging into your one or two projects to check whether you genuinely built them. Heavy system design is rare at this stage — clarity of basics and how confidently you explain your work matter far more.

At three years, interviewers test depth rather than definitions: JavaScript internals, performance optimisation (bundle size, render performance, lazy loading), state management trade-offs, testing practices, and accessibility. Frontend interview questions for 3 years of experience typically include a component-design or machine-coding round — building tabs, autocomplete, or nested comments — plus scenario questions like how you'd migrate an app to a new framework, and deeper behavioural rounds on ownership, mentoring, and delivery under deadlines.

Layer your preparation: lock JavaScript fundamentals and your primary framework first, then practise DSA at the easy-to-medium level, then do machine-coding drills until you can build a small component cleanly within a time limit. Build two resume projects you can defend end-to-end — architecture decisions, trade-offs, and measurable improvements — because product companies probe projects harder than puzzles. In the final weeks, solve company-specific frontend interview questions from past experiences and complete at least two full-length mocks, since most late-stage rejections come from communication and nerves rather than knowledge gaps.

Resume review on LinkedIn usually takes two forms: asking connections, recruiters, or open threads to critique your resume publicly, and formal review services offered by professionals on the platform. Public feedback is useful for catching first-impression issues and embarrassing errors, but comments tend to be generic because strangers don't know your target role or industry expectations. It works best as a directional check — for line-by-line rewriting and positioning against a specific job description, a focused review with someone from your target industry is far more effective.