Coding Interview Resources

Adding numbers without using '+' in Python

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Python Tools

Leetcode patterns you should definitely checkout to Learn DSA(Java) from scratch

1️⃣ Arrays: Data structures, such as arrays, store elements in contiguous memory locations. They are versatile and useful for a wide variety of purposes.
LeetCode Problems:
• Search in Rotated Sorted Array (Problem #33)
• Product of Array Except Self (Problem #238)
• Find the Missing Number (Problem #268)

2️⃣Two Pointers: In Two Pointers, two pointers are maintained in the collection and can be manipulated to solve a problem efficiently.
LeetCode problems:
• Trapping Rain Water (Problem #42)
• Longest Substring Without Repeating Characters (Problem #3)
• Squares of a Sorted Array (Problem #977)

3️⃣In-place Linked List Traversal: As an explanation, in-place traversal is a technique for modifying linked list nodes without using extra space.
LeetCode Problems:
• Remove Nth Node From End of List (Problem #19)
• Reorder List (Problem #143)

4️⃣Fast & Slow Pointers: This pattern uses two pointers to traverse a sequence at different speeds (fast and slow), often used to detect cycles or find a specific position in the sequence.
LeetCode Problems:
• Happy Number (Problem #202)
• Subarray Sum Equals K (Problem #560)
• Intersection of Two Linked Lists (Problem #160)

5️⃣Merge Intervals: This pattern involves merging overlapping intervals in a collection, often used in problems dealing with intervals or ranges.
LeetCode problems:
• Non-overlapping Intervals (Problem #435)
• Minimum Number of Arrows to Burst Balloons (Problem #452)

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DSA Interview Preparation Resources: https://topmate.io/coding/886874

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HTTPS Status Codes

List vs Tuple

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Devops Tools

Recursion is a problem-solving technique in which the solution is dependent on solutions to smaller instances of the same problem. Computing factorials is a classic example of recursive programming.

Every recursive program follows the same basic sequence of steps:

Set up the algorithm. Recursive programs frequently require a seed value, to begin with. This is accomplished by either using a parameter passed to the function or by providing a non-recursive gateway function that sets up the seed values for the recursive calculation.

Check to see if the current value(s) being processed correspond to the base case. If so, process the value and return it.

Rephrase the solution in terms of a smaller or simpler sub-problem or sub-problems.

Apply the algorithm to the sub-problem.

In order to formulate an answer, combine the results.

Return the results.

Starting a career in coding involves learning programming languages, practicing problem-solving, and building real-world projects. Here's a step-by-step guide to help you get started:

1. Choose a Programming Language

For Web Development: HTML, CSS, JavaScript

For Data Science: Python, R

For Software Development: Python, Java, C++, C#

For Mobile Development: Java/Kotlin (Android), Swift (iOS), Flutter


If unsure, start with Python—it’s beginner-friendly and widely used.


2. Learn the Fundamentals

Variables, Data Types

Loops, Conditionals

Functions, Object-Oriented Programming

Data Structures (Lists, Arrays, Dictionaries)

Algorithms (Sorting, Searching, Recursion)



3. Practice with Hands-on Projects

Web: Portfolio website, To-Do List app, Weather app

Python: Calculator, Data analysis projects, Web scraping

Game Dev: Simple 2D game (Pygame, Unity)

Mobile: Expense tracker, Notes app


Use GitHub to store projects and build a portfolio.


4. Solve Coding Challenges

LeetCode – Best for coding interviews

HackerRank – Beginner-friendly challenges

CodeWars – Fun coding puzzles



5. Learn Version Control (Git & GitHub)

Creating repositories

Pushing and pulling code

Branching and merging



6. Explore Development Tools

VS Code (Best for beginners)

PyCharm (For Python)

Eclipse/IntelliJ (For Java)

Android Studio (For Android development)



7. Get Certified (Optional)

Google IT Automation with Python

AWS Certified Developer

Microsoft Certified: Azure Developer Associate



8. Apply for Internships & Freelance Work

Look for internships or entry-level jobs

Contribute to open-source projects

Offer freelance work on Upwork, Fiverr, Freelancer



9. Network & Join Coding Communities

Join LinkedIn, Reddit (r/learnprogramming), and Stack Overflow

Contribute to GitHub open-source projects

Attend hackathons and meetups



10. Keep Learning & Growing

Explore cloud computing (AWS, Google Cloud, Azure)

Learn machine learning & AI

Stay updated with cybersecurity best practices


You can check these resources for Coding interview Preparation

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Coding and Aptitude Round before interview

Coding challenges are meant to test your coding skills (especially if you are applying for ML engineer role). The coding challenges can contain algorithm and data structures problems of varying difficulty. These challenges will be timed based on how complicated the questions are. These are intended to test your basic algorithmic thinking.
Sometimes, a complicated data science question like making predictions based on twitter data are also given. These challenges are hosted on HackerRank, HackerEarth, CoderByte etc. In addition, you may even be asked multiple-choice questions on the fundamentals of data science and statistics. This round is meant to be a filtering round where candidates whose fundamentals are little shaky are eliminated. These rounds are typically conducted without any manual intervention, so it is important to be well prepared for this round.

Sometimes a separate Aptitude test is conducted or along with the technical round an aptitude test is also conducted to assess your aptitude skills. A Data Scientist is expected to have a good aptitude as this field is continuously evolving and a Data Scientist encounters new challenges every day. If you have appeared for GMAT / GRE or CAT, this should be easy for you.

Resources for Prep:

For algorithms and data structures prep,Leetcode and Hackerrank are good resources.

For aptitude prep, you can refer to IndiaBixand Practice Aptitude.

With respect to data science challenges, practice well on GLabs and Kaggle.

Brilliant is an excellent resource for tricky math and statistics questions.

For practising SQL, SQL Zoo and Mode Analytics are good resources that allow you to solve the exercises in the browser itself.

Things to Note:

Ensure that you are calm and relaxed before you attempt to answer the challenge. Read through all the questions before you start attempting the same. Let your mind go into problem-solving mode before your fingers do!

In case, you are finished with the test before time, recheck your answers and then submit.

Sometimes these rounds don’t go your way, you might have had a brain fade, it was not your day etc. Don’t worry! Shake if off for there is always a next time and this is not the end of the world.

Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624

Credits: https://t.me/datasciencefun

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Hope this helps you 😊

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Python Loops ✅