If you happen to’re a CS pupil, chances are high you’ve got dreamt at some stage in getting an opportunity to work with the FAANG/MAANG — Meta, Amazon, Apple, Netflix, or Google. I do know making ready for these internships in 3 months may sound like a tall order, however belief me, it is doable with the proper angle and a transparent plan. Whereas your consistency and mindset rely in your private objectives, what I can assist you with is creating a transparent plan and serving to you perceive the method so you’ll be able to put together higher—as a result of the competitors is brutal. Google alone will get thousands and thousands of functions, with acceptance charges hovering round 2–3%.
So, I’ll begin with how the hiring course of works, then stroll you thru a 3-month plan together with all of the assets that’ll enable you alongside the way in which. Let’s get began.
Understanding FAANG Internship Hiring
FAANG firms have multi-stage hiring processes designed to filter for prime expertise. Understanding this course of needs to be step one in your preparation journey. The method sometimes contains:
- Software and Resume Screening: Purposes often open early (July–September) for the next summer time and fill on a rolling foundation. Your resume should cross Applicant Monitoring Methods (ATS) and catch a recruiter’s eye. Preserve it to 1 web page, emphasize related coursework/initiatives, and use metrics (e.g., “improved efficiency by 30%”) and key phrases from the job description. Many firms prioritize early functions since roles refill shortly. Referrals from workers can assist bypass preliminary filters—don’t ignore the ability of networking.
- On-line Assessments: Most FAANGs begin with coding assessments on platforms like HackerRank or LeetCode. These assess your problem-solving and coding expertise, sometimes specializing in information buildings and algorithms. For information science roles, count on each coding (Python/SQL) and ML/statistics questions, together with case/problem-solving duties.
- Technical Interviews: Anticipate 2–4 rounds of reside coding interviews, typically by way of video name. You’ll resolve DSA issues whereas explaining your thought course of, together with time/house complexity evaluation. Some firms could embody system design questions, particularly for extra senior roles.
- Behavioral Interviews: These give attention to smooth expertise, cultural match, and motivation (e.g., Amazon’s Management Rules or Meta’s STAR-format “Inform me a couple of time…” questions).
- Crew Matching (if relevant): Some FAANGs, like Amazon, match candidates with groups after interviews, which can contain extra conversations. Be prepared with 2–3 strong venture examples to speak about.
Month 1: Constructing a Sturdy Basis
Week 1-2: Be taught Core DSA and Coding Fundamentals
FAANG interviews rely closely on DSA. Getting comfy with core buildings early units you up for extra superior matters. Begin by mastering elementary information buildings: arrays, linked lists, stacks, queues, and hash maps. Perceive how they work and when to make use of them.
Choose one programming language—Python is usually most well-liked for its simplicity and is broadly utilized in interviews. Begin fixing simple LeetCode issues like “Two Sum” or “Reverse Linked Record.” Grind75 is a good (free) useful resource. Purpose for 1–2 issues a day.
Week 3-4: Superior DSA Half I and Beginning Mock Interviews
Transfer on to extra complicated buildings like timber, graphs, and sorting algorithms (e.g., binary search, quicksort). Be taught traversals (e.g., in-order, pre-order) and fundamental graph algorithms like DFS. Begin fixing 2–3 medium LeetCode issues each day, specializing in patterns like two pointers or sliding window.
Begin mock interviews. Pramp.com gives free peer-to-peer interviews. Do 1–2 mock periods to get suggestions in your explanations. I additionally suggest neetcode.io for clear explanations of LeetCode issues.
Month 2: Apply, Apply and Apply + Begin Networking
Week 5-6: Superior DSA Half II and Construct Tasks
Examine dynamic programming, backtracking, and extra superior graph algorithms like BFS and Dijkstra’s algorithm. These typically present up in exhausting interview issues. Resolve 3–4 medium-to-hard issues each day and evaluate optimized options.
Begin engaged on 1–2 private initiatives (like a full-stack net app or a Python recreation) to point out initiative in case you don’t have prior internship expertise. Be sure your initiatives are clear, documented, and spotlight your influence. AlgoExpert is an efficient paid platform for DP/graph visible learners.
Week 7-8: System Design, Behavioral Prep and Networking
If you happen to’re a junior or rising senior, system design is much less prone to be examined. However in case you’re making use of for extra superior intern roles, study the fundamentals (e.g., design a URL shortener). Google may ask easy design questions, whereas Meta typically focuses on scale.
Construct a one-page resume with job-related key phrases like “Python,” “AWS,” or “full-stack.” Join with 5–10 FAANG workers weekly on LinkedIn. Ask for informational chats or referrals—a easy message like “I utilized for [X intern role] – would you be open to referring me?” works.
Begin prepping for behavioral interviews. Write out 3–5 STAR-format tales targeted on challenges, teamwork, management, and failures. Adapt your tales to firm cultures (e.g., Amazon’s Management Rules, Google’s “8 Be’s,” or Meta’s Possession worth). Apply “Inform me about your self” and “Why [Company]?”
Month 3: Mock Interviews and Purposes
Week 9-10: Mock Interviews and Talent Refinement
That is crunch time. Simulate actual interviews—do full loops (3–4 questions) with deadlines. Interviewing.io gives mock interviews with FAANG engineers ($200–300 per session, scholarships obtainable). In any other case, use free choices like Pramp or pair up with a good friend.
Focus extra on evaluation than amount now. Evaluate your errors, polish your STAR solutions, and apply delivering solutions clearly and concisely.
Week 11-12: Apply and Last Interview Prep
Steadiness intense prep with relaxation. Get correct sleep, eat properly, and keep away from burnout. Use the Pomodoro methodology to remain on observe.
Apply to all FAANG firms by means of their portals, and comply with up with referrals wherever doable. Be sure your LinkedIn, GitHub, and portfolio are polished—interviewers could test.
If you happen to’re already interviewing someplace, give attention to nailing these. Comply with up politely with recruiters in case you haven’t heard again. And don’t overlook to plan a small reward after interviews (a brief journey or dinner out) to remain motivated.
Conclusion: Assets and Examine Aids
- Coding Apply: LeetCode (particularly Medium/Arduous issues), HackerRank, InterviewBit. Books: Cracking the Coding Interview, Components of Programming Interviews
- On-line Programs:
- Coursera: Algorithms Specialization (Princeton)
- Udemy: Grokking the Coding Interview
- MIT OpenCourseWare, Harvard’s CS50
- Information science prep: Coursera (Andrew Ng’s ML), Kaggle programs, DataCamp tutorials, Kaggle competitions
- Mock Interview Platforms: Pramp, interviewing.io, CareerCup boards, DesignGurus
- Resume Assist: Glassdoor blogs, InternStreet, LifeAt pages. Use Julia Evans’ “Brag Doc” methodology to craft bullet factors
- Networking Avenues: LinkedIn, alumni networks, campus profession facilities, engineering golf equipment, tech meetups, on-line communities like Slack/Discord teams
- Motivation & Time Administration: Pomodoro timers (apps or browser extensions). Examine schedules (Google Calendar reminders or a Trello board). Communities: Be part of or kind a research group to remain accountable (as InternStreet suggests, pair programming or group research). Learn blogs of different interns (like this one) for inspiration
Kanwal Mehreen Kanwal is a machine studying engineer and a technical author with a profound ardour for information science and the intersection of AI with drugs. She co-authored the book “Maximizing Productiveness with ChatGPT”. As a Google Era Scholar 2022 for APAC, she champions range and tutorial excellence. She’s additionally acknowledged as a Teradata Variety in Tech Scholar, Mitacs Globalink Analysis Scholar, and Harvard WeCode Scholar. Kanwal is an ardent advocate for change, having based FEMCodes to empower ladies in STEM fields.
