├── housing ├── ISI Apartment Guide, 2021 (1).xlsx └── README.md ├── flight-booking └── README.md ├── forex └── README.md ├── immigration-questions └── README.md ├── on-campus-jobs └── README.md ├── pre-departure-docs └── README.md ├── README.md ├── pre-arrival-tasks └── README.md ├── course-reviews ├── README.md └── Own_Course_Reviews.MD ├── .gitignore └── internships-and-fulltime └── README.md /housing/ISI Apartment Guide, 2021 (1).xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Anirudh257/AttendingUnivesityOfCaliforniaAtRiverside/HEAD/housing/ISI Apartment Guide, 2021 (1).xlsx -------------------------------------------------------------------------------- /flight-booking/README.md: -------------------------------------------------------------------------------- 1 | ## Tips to follow while booking flights 2 | 3 | 1. Try booking in groups. 4 | 5 | 2. Don’t select seats when you book flight, select on the day itself and try to book seat which doesn’t have anyone near you. 6 | 7 | 3. Prefer known carriers. 8 | 9 | 4. Anything more than 2 hr layover is just fine. 10 | -------------------------------------------------------------------------------- /forex/README.md: -------------------------------------------------------------------------------- 1 | ## Tips before booking Forex Card 2 | 3 | 1. Ask your loan provider for a Forex Card. 4 | 5 | 2. Avoid using forex after arriving in the US. 6 | 7 | 3. Always have a point of contact handy. 8 | 9 | 4. **Forex Card Options** : SBM & Niyo Global - Lowest loading fee. 10 | 11 | 5. Not recommended - Indus. 12 | -------------------------------------------------------------------------------- /immigration-questions/README.md: -------------------------------------------------------------------------------- 1 | ## Possible Questions asked during Immigration 2 | 3 | 1. What is the purpose of your visit to US? 4 | 5 | 2. Which university are you attending? 6 | 7 | 3. How far is Riverside and how do you plan to go there? 8 | 9 | 4. Where are you going to stay in Riverside? (Keep a copy of your lease and keep your address in mind). 10 | 11 | 5. Prescription of special medicines if any. 12 | -------------------------------------------------------------------------------- /housing/README.md: -------------------------------------------------------------------------------- 1 | ## Important Tips on Housing 2 | 3 | * A good resource to find different housing options can be found [here](https://docs.google.com/spreadsheets/d/1W733qxThpY85sFvdtwqIgfTo8M7L_X367VxTHVOBUYM/edit#gid=1442012155) and [here](https://github.com/Anirudh257/AttendingUnivesityOfCaliforniaAtRiverside/blob/main/housing/ISI%20Apartment%20Guide%2C%202021%20(1).xlsx). 4 | 5 | * **Apply for housing immediately after receiving your admission, possibly in June/July.** 6 | 7 | * If you are an international MS student, the chances of getting on-campus housing are very low. It is always better to keep other options open. 8 | 9 | -------------------------------------------------------------------------------- /on-campus-jobs/README.md: -------------------------------------------------------------------------------- 1 | ## On campus Job Tips 2 | 3 | 1. Best way to apply for on campus jobs is via [Handshake](https://ucr.joinhandshake.com/) 4 | 5 | 2. **Dining job** is generally easier to get. 6 | 7 | 3. **Readers/Graders job :** available in [large numbers](https://graduate.ucr.edu/list-projected-ta-positions). It involves grading the assignments of the courses. Tips to follow are: 8 | 9 | * Mail the professors, 15-20 days before start of quarter. 10 | 11 | * Add your transcripts/expertise/interest in the email. 12 | 13 | * Only 9h/week. 14 | 15 | 4. **Research Assistant / Teaching Assistant :** Only for PhDs and not applicable for MS students in the first quarter. Build a rapport with profs in the first quarter. Luck-based system 16 | with no guarantee. 17 | 18 | 5. **Successful completion of the course, and career outcomes post graduation are important than on campus part-time jobs.** 19 | -------------------------------------------------------------------------------- /pre-departure-docs/README.md: -------------------------------------------------------------------------------- 1 | ## Very Important Documents to be kept in the handbag 2 | 3 | | S No. | Name | 4 | |-------|---------------------------------------------------------------------------------------| 5 | | 1 | Passport with Visa Page | 6 | | 2 | Air Tickets | 7 | | 3 | Admission Letter | 8 | | 4 | Any Scholarship Letter | 9 | | 5 | Fee Receipt | 10 | | 6 | Report of Immunization | 11 | | 7 | I-20 | 12 | | 8 | Sevis Fee Receipt | 13 | | 9 | Book for flight reading | 14 | | 10 | Accommodation Confirmation | 15 | | 11 | Airport Pickup Details / Direction Map | 16 | | 12 | Foreign Exchange Receipt | 17 | | 13 | Address book with contacts of University Staff, Students and Friends/Relatives abroad | 18 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Attending the University Of California At Riverside 2 | 3 | This repo is inspired from the excellent [AttendingUniversityAtBuffalo](https://github.com/snigi-gupta/AttendingUniversityAtBuffalo) which collates important resources and advice that the author, [Snigdha Gupta](https://gist.github.com/snigi-gupta/04307be1585712b0410f91061ea16cb5) found useful during her stay at UB. To avoid duplicity, I will only add resources that are specific to UC Riverside. This repo will receive continuous updates in the future. 4 | 5 | A lot of this content is taken from amazing slides/talks by [Naman Mital](https://www.mittalnaman.com/) and [Rugved Bhise](https://rugvedb133.github.io/) 6 | 7 | Join this amazing [discord server](https://discord.gg/G5u7jqQtmU) made by [Naman Mital](https://www.mittalnaman.com/) for UCR and general MS queries. 8 | 9 | ## Contents 10 | * [UCR Academic Calendar](https://registrar.ucr.edu/calendar) 11 | 12 | * [Course reviews and advice](/course-reviews) 13 | 14 | * [Registering for courses at UCR](https://www.youtube.com/watch?v=kwZJ8vO4Yug) 15 | 16 | * [Tuition & Fees at UCR](https://registrar.ucr.edu/tuition-fees) 17 | 18 | * [Important documents in handbag](/pre-departure-docs) 19 | 20 | * [Pre-arrival tasks](/pre-arrival-tasks) 21 | 22 | * [Housing](/housing) 23 | 24 | * [Flight booking](/flight-booking) 25 | 26 | * [Forex options](/forex) 27 | 28 | * [Immigration questions](/immigration-questions) 29 | 30 | * [On-campus jobs](/on-campus-jobs) 31 | 32 | * [Internshps & Full-time opportunities](/internships-and-fulltime) 33 | 34 | ## Contribute 35 | If you're a current or former Student, Faculty, or a Staff member at UCR, contribute by submitting a pull request. 36 | 37 | -------------------------------------------------------------------------------- /pre-arrival-tasks/README.md: -------------------------------------------------------------------------------- 1 | ## Things to do before going to UCR 2 | 3 | 1. Confirm accommodation booking. 4 | 5 | 2. Arrange Foreign Exchange & Student Medical Insurance. 6 | 7 | 3. Inform University about flight arrival details and confirm airport pickup, if available. 8 | 9 | 4. Contact airline for baggage dimensions and weight. 10 | 11 | 5. [Check what you can bring to the US](https://www.tsa.gov/travel/security-screening/whatcanibring/all). 12 | 13 | 6. Reconfirm reservation with agent and the airlines 72 hours before departure. 14 | 15 | 7. Ask travel agent for arranging Veg / Non-Veg food on flight and confirm it. 16 | 17 | 8. Make a list of items packed in each bag. 18 | 19 | 9. Get a complete medical check up – Dental, ENT, Physical, Chest X-Ray, etc. 20 | 21 | 10. Get all [required vaccination](https://studenthealth.ucr.edu/Immunization) as mandated by UCR. 22 | 23 | 11. Keep a copy of all the documents at home. (eg. Marksheets, Admission Letter, Passport, Transcripts, Records, Fee Receipt, Forex Receipt, etc.) 24 | 25 | 12. Leave a copy of the medical documents. 26 | 27 | 13. Leave a list of contact addresses & phone numbers at home. 28 | 29 | 14. Leave a few “Authority Letters”, blank signed letters at home – parents may need them to continue transaction on your behalf. 30 | 31 | 15. Open a joint bank account. 32 | 33 | 16. Get a mobile phone / tab / laptop with webcam and video-conferencing facility. 34 | 35 | 17. Buy textbooks only if absolutely necessary. 36 | 37 | 18. ~~Get International Driving License~~ California allows use of any home country or state issued Driving Licence. 38 | 39 | 19. Get an Indian Credit Card for emergency use. 40 | 41 | 20. Get a good haircut. 42 | 43 | 21. Medical Reports and Prescriptions. 44 | 45 | 22. Note Parents Account Number. 46 | 47 | 23. Copy of Visa, Passport and Admission Letter in all bags. 48 | 49 | -------------------------------------------------------------------------------- /course-reviews/README.md: -------------------------------------------------------------------------------- 1 | ## Course Reviews 2 | 3 | 1. [General UCR Course Difficulty Database](https://docs.google.com/spreadsheets/d/1qiy_Oi8aFiPmL4QSTR3zHe74kmvc6e_159L1mAUUlU0/edit#gid=0) 4 | 5 | 2. [UCR Grad CS Course Difficulty Reviews](https://docs.google.com/spreadsheets/d/17ovp5iLEcPAA3S19mD7oKel99CmkNn0l/edit#gid=1532022067) 6 | 7 | 3. [My own course experiences](Own_Course_Reviews.MD) 8 | 9 | ### Important advice from seniors 10 | 11 | * Register for the courses as soon as possible as the enrollment is on a First Come First Serve basis. UCR provides a waiting list for most of the courses. Enroll on a waiting list if the course is full. 12 | 13 | * UCR follows a quarter system instead of a usual semester system. This implies that most courses are just 10 weeks long and hence it is important to keep the course load optimal. Take only one core/hard course per quarter. 14 | 15 | * Examples of hard courses - Machine Learning, Design & Analysis of Algorithms, DBMS, Advanced OS, Architecture etc. If you are taking a hard course, combine it with easier courses. 16 | 17 | * Avoid hard courses in the first quarter. 18 | 19 | * [Rate My Professors](https://www.ratemyprofessors.com/search/teachers?query=*&sid=1076) is a good resource for understanding a professor's class. 20 | 21 | * An excellent advice from https://www.snigdhagupta.com/ was to select courses based on your career objectives. For example, if your goal is to become a backend engineer, courses like **distributed systems**, and **principles of computing** should be in your course list. For ML Engineers, courses like **Machine Learning**, and **Natural Language Processing** should be a part of the course list. 22 | 23 | * There are three ways for completion of your MS CS coursework as mentioned in https://www1.cs.ucr.edu/programs/graduate/computer-science-masters 24 | 25 | * **If your objective is to get a job, focus on finishing your courses via the Comprehensive Exam option.** Take up the **project option** only if you are sure to finish it within your course period. 26 | 27 | * **Thesis** is time-consuming and equivalent to a workload of 3 or more courses. **Take it only if you can devote this time.** This is a good option for people who want to do academia in the future or enter research engineering roles. 28 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Created by https://www.toptal.com/developers/gitignore/api/intellij 2 | # Edit at https://www.toptal.com/developers/gitignore?templates=intellij 3 | 4 | ### Intellij ### 5 | # Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio, WebStorm and Rider 6 | # Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839 7 | 8 | # User-specific stuff 9 | .idea/**/workspace.xml 10 | .idea/**/tasks.xml 11 | .idea/**/usage.statistics.xml 12 | .idea/**/dictionaries 13 | .idea/**/shelf 14 | 15 | # AWS User-specific 16 | .idea/**/aws.xml 17 | 18 | # Generated files 19 | .idea/**/contentModel.xml 20 | 21 | # Sensitive or high-churn files 22 | .idea/**/dataSources/ 23 | .idea/**/dataSources.ids 24 | .idea/**/dataSources.local.xml 25 | .idea/**/sqlDataSources.xml 26 | .idea/**/dynamic.xml 27 | .idea/**/uiDesigner.xml 28 | .idea/**/dbnavigator.xml 29 | 30 | # Gradle 31 | .idea/**/gradle.xml 32 | .idea/**/libraries 33 | 34 | # Gradle and Maven with auto-import 35 | # When using Gradle or Maven with auto-import, you should exclude module files, 36 | # since they will be recreated, and may cause churn. Uncomment if using 37 | # auto-import. 38 | # .idea/artifacts 39 | # .idea/compiler.xml 40 | # .idea/jarRepositories.xml 41 | # .idea/modules.xml 42 | # .idea/*.iml 43 | # .idea/modules 44 | # *.iml 45 | # *.ipr 46 | 47 | # CMake 48 | cmake-build-*/ 49 | 50 | # Mongo Explorer plugin 51 | .idea/**/mongoSettings.xml 52 | 53 | # File-based project format 54 | *.iws 55 | 56 | # IntelliJ 57 | out/ 58 | 59 | # mpeltonen/sbt-idea plugin 60 | .idea_modules/ 61 | 62 | # JIRA plugin 63 | atlassian-ide-plugin.xml 64 | 65 | # Cursive Clojure plugin 66 | .idea/replstate.xml 67 | 68 | # SonarLint plugin 69 | .idea/sonarlint/ 70 | 71 | # Crashlytics plugin (for Android Studio and IntelliJ) 72 | com_crashlytics_export_strings.xml 73 | crashlytics.properties 74 | crashlytics-build.properties 75 | fabric.properties 76 | 77 | # Editor-based Rest Client 78 | .idea/httpRequests 79 | 80 | # Android studio 3.1+ serialized cache file 81 | .idea/caches/build_file_checksums.ser 82 | 83 | ### Intellij Patch ### 84 | # Comment Reason: https://github.com/joeblau/gitignore.io/issues/186#issuecomment-215987721 85 | 86 | # *.iml 87 | # modules.xml 88 | # .idea/misc.xml 89 | # *.ipr 90 | 91 | # Sonarlint plugin 92 | # https://plugins.jetbrains.com/plugin/7973-sonarlint 93 | .idea/**/sonarlint/ 94 | 95 | # SonarQube Plugin 96 | # https://plugins.jetbrains.com/plugin/7238-sonarqube-community-plugin 97 | .idea/**/sonarIssues.xml 98 | 99 | # Markdown Navigator plugin 100 | # https://plugins.jetbrains.com/plugin/7896-markdown-navigator-enhanced 101 | .idea/**/markdown-navigator.xml 102 | .idea/**/markdown-navigator-enh.xml 103 | .idea/**/markdown-navigator/ 104 | 105 | # Cache file creation bug 106 | # See https://youtrack.jetbrains.com/issue/JBR-2257 107 | .idea/$CACHE_FILE$ 108 | 109 | # CodeStream plugin 110 | # https://plugins.jetbrains.com/plugin/12206-codestream 111 | .idea/codestream.xml 112 | 113 | # Azure Toolkit for IntelliJ plugin 114 | # https://plugins.jetbrains.com/plugin/8053-azure-toolkit-for-intellij 115 | .idea/**/azureSettings.xml 116 | 117 | # End of https://www.toptal.com/developers/gitignore/api/intellij -------------------------------------------------------------------------------- /course-reviews/Own_Course_Reviews.MD: -------------------------------------------------------------------------------- 1 | 2 | Similar to [Snigdha's course reviews](https://github.com/snigi-gupta/AttendingUniversityAtBuffalo/blob/main/Computer%20Science%20Important%20Tips/CourseReview.md), I have collated mine and my friends' course experiences that can help incoming and current students in their course selection. Feel free to add a pull-request if you want to add your own experiences! 3 | 4 | **Disclaimer: This is my own experience. Take your decision with more research.** 5 | 6 | | Subject | Student Review | 7 | --- | -- | 8 | **Advanced OS by Dr. Kim** | As a CS student, I had to take 2 out of 3 core courses and I chose Operating Systems as I enjoyed it as an undergraduate. While this course has commonalities with my previous course, it was more rigorous and I had to spend significant time on my labs. There are multiple graded components in this course: Examinations, Paper reviews, Labs. It is important to choose good team members as finishing the labs along with your coursework can get very hectic. The examinations are straightforward and the professor clearly explains what questions are going to come in the examinations. The critiques can be demanding. I think that this was an easily-scoring core course than its counterparts. **Preferably, take lighter courses along with this course.** Some nuggets of advice from my end are: a) Manage your time efficiently as the quarter system gets over quickly and the labs/critique reviews require sufficient time and effort. b) If you are struggling with the course, talk to the TAs, they are very helpful :). c) I really liked [Udacity's OS courses](https://www.udacity.com/course/advanced-operating-systems--ud189) that acts a good review for similar topics. [Neso Academy's OS Playlist](https://www.youtube.com/playlist?list=PLBlnK6fEyqRiVhbXDGLXDk_OQAeuVcp2O) is also good if you have doubts. 9 | **Big Data Management by Dr. Eldawy** | Big Data is one of the hot areas with an abundance of job opportunities. The professor does a great job updating the course with industry standards and covers relevant topics like NoSQL, Parquet, RDBMS, Hadoop, etc. For people looking for a job after MS, it is extremely useful! The course content is light and the examinations are easy to score. The main component of this course is the project which accounts for **50%** of the grades. My only advice here is to choose a strong team and distribute the work accordingly. Start working on the project as soon as you decide the topic. If you are a beginner to this field, ask the prof for relevant ideas and seniors/industry professionals for good ideas. A good project done here can help you stand apart from the crowd! 10 | **Scientific Computing by Dr. Shinar** | This course is an excellent primer to Linear Algebra and the mathematical underpinnings behind Machine Learning, Graphics and other areas. The course can become too fast-paced for many people. It is highly recommended for people getting into research or preparing for ML interviews. Don't take it if you don't like Mathematics. There are many mathematics-proof based assignments in this course. To do well in this course, attend all the classes and take rigorous notes and don't leave things till the last day. I found [Numerical methods](https://www.coursera.org/learn/numerical-methods-engineers#syllabus) and [Applied Linear Algebra & Numerical Analysis](https://faculty.washington.edu/kutz/am584/am584.html) useful for reviewing some topics. 11 | **Foundations of Machine Learning by Dr. Roy-Chowdhury** | Machine learning is a fast growing field that is disrupting many industries. Plenty of roles require knowledge of Machine Learning like Machine Learning Engineer, Data Scientist, Data Engineers and many more. Irrespective of your objective to enter the industry or continue in the academia, this course is a must. The content covered in the course was extremely beneficial to me in my interviews. This is a fundamental course covering the Mathematical underpinnings and gives a broad overview of the various Machine Learning algorithms. While the assignments are mathematically rigorous, quizzes and examinations are easy. **This course is not trivial and do not leave anything till the last moment.** If you have weak Mathematical foundations, do this course: [MIT Probability course](https://www.youtube.com/playlist?list=PLUl4u3cNGP60hI9ATjSFgLZpbNJ7myAg6). 12 | **Natural Language Generation by Dr. Yue Dong** | Natural Language Generation is a subfield of Artificial Intelligence with widespread applications in customer service, marketing, news article summarization, etc. Being a seminar course, there are no examinations and only a project is required. The course also covers novel Natural Language Generation research works. Making a good project in this course will enhance your resume and make you a good fit for many companies. Being a quarter course, it is better to decide and start working on a topic as soon as possible. If you are a beginner in NLP, check out this [Stanford NLP course](https://www.youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ). **I would recommend complete beginners in Machine Learning against taking up this course**. 13 | **Advanced Computer Vision by Dr. Amit Roy Chowdhury** | DALLE-3, Diffusion are all built on Computer Vision and Language modalities. It gives a brief overview of the various fields in Computer Vision. There are no examinations in this course but a lot of assignments. Having prior experience in the field is not mandatory but the assignments can get very challenging. The topics in the course were extremely helpful for my interviews in ML companies. No book is followed in this course but one can look at [First Principles of Computer Vision](https://fpcv.cs.columbia.edu/). 14 | **Reinforcement Learning by Dr. Nanpeng Yu** | RL is another subfield of artificial intelligence getting a lot of attention these days. It has many applications, in gaming and **RLHF**. Many robotics companies have roles using **RL**. Being a seminar course, there were no examinations but there was a project and assignments. I found the course heavy for the quarter system and advice beginners to not take it. Some good online resources are: [Deepmind's RL lectures](https://www.deepmind.com/learning-resources/reinforcement-learning-lecture-series-2021) and [IIT Madras RL course](https://www.youtube.com/playlist?list=PLEAYkSg4uSQ0Hkv_1LHlJtC_wqwVu6RQX). 15 | **Introduction to Deep Learning by Dr. Samet Omyak** | Deep Learning(DL) is one of the major reasons behind ML's popularity and success across various fields. I found the courseload hectic due to six assignments and one final examination along with a final project. It is not advisable to take in the final quarter. Also, people with no prior knowledge will find it difficult. [Stanford's CS231n](http://cs231n.stanford.edu/) course is a great resource for self-study. 16 | **Design and Analysis of Algorithms by Dr. Amey Bhangale** | Algorithms is one of the most important topics in Computer Science, irrespective of your domain of interest: machine learning, cybersecurity, etc. I highly recommend to take this course within your time in UCR. Different profs have differing philosophy in teaching this course. Coming from a theoretical background, Prof Amey introduces important concepts like P=NP, approximation algorithms, etc. If you take it under a different prof like Dr. Yan Gu/Dr. Yihan Sun, it will be more practical and coding-based. I enjoyed taking the course under Prof Amey as I understood the logic behind dynamic programming and optimization. Nonetheless, I have heard raving reviews of Dr. Gu and Dr Sun's course-structure as well. 17 | -------------------------------------------------------------------------------- /internships-and-fulltime/README.md: -------------------------------------------------------------------------------- 1 | 2 | # Internships & Full-Time Opportunities 3 | 4 | ## General Advice 5 | 6 | * UCR's Fall Quarter starts late in September compared to August in most other universities. 7 | * Start applying to internships or full-time opportunities early in August i.e., when you're still in your home country. This may put you at the same level as students at other universities who start earlier. 8 | * Networking and referrals are vital in getting an interview call from your dream organization. 9 | * Attend large-scale networking events like [GHC](https://ghc.anitab.org/)[**Women only**], [SWE](https://swe.org/)[**Society of Women Engineers**][**Women only**]. Look into these resources: 10 | * https://medium.com/womenintechnology/how-to-get-the-most-out-of-grace-hopper-celebration-2023-63291dfbda70 11 | * https://www.youtube.com/watch?v=sF6izpB_A0Y&pp=ygUKeXVkaSBqIGdoYw%3D%3D 12 | * Use [LinkedIn](https://www.linkedin.com) for networking, referrals and applying. Check this for advice related to optimizing [Linkedin](https://www.linkedin.com/posts/sanjay-kumar-vishwakarma_internationalstudents-incoming-msinusa-activity-6955536904423436289-yk8r/?utm_source=linkedin_share&utm_medium=member_desktop_web) 13 | * Some great advice on resumes can be found here: https://blog.dataengineer.io/p/how-to-craft-the-perfect-data-engineer 14 | * Don't underestimate the power of an effective cold-email. Getting the attention of the hiring manager/HR via a well-written cold email would go a long way in getting a callback. I found the advice mentioned here helpful: https://www.indeed.com/career-advice/finding-a-job/cold-email-for-job. A good template can be found here: https://uvasrg.github.io/prospective/ which can be modified depending on the job type. 15 | * Use [levels.fyi](https://www.levels.fyi) for salary information. 16 | * Monitor [summer2023-internships](https://github.com/pittcsc/Summer2023-Internships) for summer 2023 internships. 17 | * Learn the art of negotiation. Don't accept an offer without negotiation. Check https://haseebq.com/my-ten-rules-for-negotiating-a-job-offer/ for good advice. 18 | 19 | ## Preparation Advice 20 | 21 | * Pick any programming language - C++/Java/Python/JavaScript etc. and master it. 22 | * Brush up your Algorithms & Data Structures. 23 | * Enter [leetcode](https://www.leetcode.com). 24 | * [Neetcode.io](https://neetcode.io/practice) has an excellent compilation of problems for interview preparation. If you're already good at DSA, go for **Blind 75**. If you're relatively a novice, go for **NeetCode 150** 25 | * These 75 or 150 problems teach you the most common patterns of questions asked in tech interviews. The goal is not to remember solutions but to be able to recognize a pattern from a new problem and be able to solve it. 26 | * Start working on problems for each pattern you practice. There's always a compilation of problems grouped by patterns. For example, [this post](https://leetcode.com/discuss/career/448285/List-of-questions-sorted-by-common-patterns). 27 | * After you're confident about your depth and breadth of theory and problems, start applying to companies. 28 | * Now, start targeted practice. Every company has its way of assessing candidates. Leetcode provides a compilation of the most frequently asked interview questions, grouped by companies. 29 | * If you're targeting SDE2 / SE2 / Senior SDE - a strong grip on System Design is necessary. 30 | * Start System Design preparation with [this post](https://github.com/donnemartin/system-design-primer) and then [this book](https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable/dp/1449373321). 31 | * Most of the interview questions focus on - Trees, Graphs, Arrays, Strings, Recursion, Binary Search, Linked Lists & Back Tracking. 32 | 33 | ## Machine-Learning specific advice 34 | 35 | * Compared to software engineering, machine-learning interviews have fewer resources. 36 | * Before preparing for an ML role, it is imperative to know the actual requirements. For example, does it require building pipelines/ or deploying ML models/or is it more research-focused? 37 | * A good way to revise fundamentals is to do ML courses in your degree. 38 | * The popularity of ML has led to an explosion of roles across various domains like LLMs, Generative AI, etc. Some roles have an explicit **MS** or **PhD** requirement (mostly research-oriented), but many have relaxed requirements. **Don't apply to a role if you don't meet these basic requirements**. 39 | * **In my opinion, the best way to improve the chances of callbacks is to do relevant projects in the domain**. For example, if the role specifically mentions LLMs, and you haven't worked on it, the chances of a callback is minimal. 40 | * Most ML interviews comprise of these 5 rounds: 41 | 42 | | Type of Round | Resources | 43 | | -------- | ------- | 44 | | Coding | Similar to the software-engineer role. If you are a beginner, consider https://www.educative.io/courses/grokking-coding-interview-patterns-java. **Practicing all the patterns is the key.** | 45 | | ML coding | Code ML algorithms from scratch like Logistic Regression, Linear Regression, etc. A good list is found here: https://github.com/alirezadir/Machine-Learning-Interviews/blob/main/src/MLC/ml-coding.md | 46 | | ML system design | It is similar to the system design round in the software engineering interview. Some recommended resources are https://www.amazon.com/Machine-Learning-System-Design-Interview/dp/1736049127 | 47 | |ML Breadth| Testing of basic ML fundamentals like gradient descent, linear regression, etc. Check Chapter 7 of https://huyenchip.com/ml-interviews-book/contents/7.1-basics.html. | 48 | |ML depth | It is more specific to your projects in the resume. For example, if you have worked primarily with NLP, expect questions on BERT, Transformer model. **Know the ins and outs of every project mentioned in your resume.** | 49 | |Behavioural | These questions gauge your personality and how you overcame challenges. Follow the **STAR** formula to answer questions as noted here: https://gist.github.com/katiestutts/7aef5063ba93616a594ac3f3764f8788. Another good resource is: https://www.interviewkickstart.com/career-advice/situational-scenario-based-interview-questions-answers. | 50 | 51 | * Some companies might focus more on MLE and hence focus more on **ML coding** and **ML System design** rounds. More **research-oriented roles** will focus on **ML depth**. **There is no hard and fast rule**. 52 | 53 | ## Resources 54 | 55 | * **Tip**: Just a list of resources. Grinding everything will not land you a job. Focus and targeted practice are key. 56 | 57 | * [Technical Interviews - Developer-Y](https://github.com/Developer-Y/technical-interviews). 58 | 59 | * Some other resources that I found useful for my ML interviews are: 60 | * https://huyenchip.com/ml-interviews-book/ [Good book for ML fundamentals]. 61 | * https://www.amazon.com/Designing-Machine-Learning-Systems-Production-Ready/dp/1098107969 [ML System Design] 62 | * https://www.amazon.com/Machine-Learning-System-Design-Interview/dp/1736049127 [ML System Design] 63 | * https://www.educative.io/courses/grokking-the-machine-learning-interview [ML System Design] 64 | * https://github.com/alirezadir/Machine-Learning-Interviews [Good compilation of resources] 65 | * https://github.com/khangich/machine-learning-interview [Good compilation of interview experiences]. 66 | * https://github.com/youssefHosni/Data-Science-Interview-Questions-Answers [Good for specific roles like Computer Vision/Data science]. 67 | * https://github.com/stas00/ml-engineering [MLE specific tips]. 68 | * https://madewithml.com/ [MLOPs related course]. 69 | * https://eugeneyan.com/ [Recsys relevant advice]. 70 | * https://davidstutz.de/how-i-prepared-for-deepmind-and-google-ai-research-internship-interviews-in-2019/ [How to prepare for research interview] 71 | * https://www.deep-ml.com/ [ML coding questions] 72 | * https://github.com/asiddhant/ai_interview_prep_notes_mar_2025 [Staff ML Engineer's Experience] 73 | --------------------------------------------------------------------------------