🌳 DFS vs BFS : Choose Right in 10 Seconds
👉 DFS (Stack/Recursion): Goes deep first. Great for path existence, cycle detection, or "any valid path".
👉 BFS (Queue): Level by level. Best for shortest path in unweighted graph or "minimum steps".
🗯 Interview Encounter: "Number of islands" or "Shortest path in maze" → BFS wins. "Validate BST" or "Clone graph" → DFS is natural.
✅ Pro Tip: Tell interviewer: “I’ll use BFS for shortest, DFS for space efficiency.” Always mention visited set to avoid cycles. Dry-run small example verbally.
👉 DFS (Stack/Recursion): Goes deep first. Great for path existence, cycle detection, or "any valid path".
👉 BFS (Queue): Level by level. Best for shortest path in unweighted graph or "minimum steps".
🗯 Interview Encounter: "Number of islands" or "Shortest path in maze" → BFS wins. "Validate BST" or "Clone graph" → DFS is natural.
✅ Pro Tip: Tell interviewer: “I’ll use BFS for shortest, DFS for space efficiency.” Always mention visited set to avoid cycles. Dry-run small example verbally.
❤2
SQL Interview Questions with Answers
1. How to change a table name in SQL?
This is the command to change a table name in SQL:
ALTER TABLE table_name
RENAME TO new_table_name;
We will start off by giving the keywords ALTER TABLE, then we will follow it up by giving the original name of the table, after that, we will give in the keywords RENAME TO and finally, we will give the new table name.
2. How to use LIKE in SQL?
The LIKE operator checks if an attribute value matches a given string pattern. Here is an example of LIKE operator
SELECT * FROM employees WHERE first_name like ‘Steven’;
With this command, we will be able to extract all the records where the first name is like “Steven”.
3. If we drop a table, does it also drop related objects like constraints, indexes, columns, default, views and sorted procedures?
Yes, SQL server drops all related objects, which exists inside a table like constraints, indexes, columns, defaults etc. But dropping a table will not drop views and sorted procedures as they exist outside the table.
4. Explain SQL Constraints.
SQL Constraints are used to specify the rules of data type in a table. They can be specified while creating and altering the table. The following are the constraints in SQL: NOT NULL CHECK DEFAULT UNIQUE PRIMARY KEY FOREIGN KEY
@coding_interview_preparation
1. How to change a table name in SQL?
This is the command to change a table name in SQL:
ALTER TABLE table_name
RENAME TO new_table_name;
We will start off by giving the keywords ALTER TABLE, then we will follow it up by giving the original name of the table, after that, we will give in the keywords RENAME TO and finally, we will give the new table name.
2. How to use LIKE in SQL?
The LIKE operator checks if an attribute value matches a given string pattern. Here is an example of LIKE operator
SELECT * FROM employees WHERE first_name like ‘Steven’;
With this command, we will be able to extract all the records where the first name is like “Steven”.
3. If we drop a table, does it also drop related objects like constraints, indexes, columns, default, views and sorted procedures?
Yes, SQL server drops all related objects, which exists inside a table like constraints, indexes, columns, defaults etc. But dropping a table will not drop views and sorted procedures as they exist outside the table.
4. Explain SQL Constraints.
SQL Constraints are used to specify the rules of data type in a table. They can be specified while creating and altering the table. The following are the constraints in SQL: NOT NULL CHECK DEFAULT UNIQUE PRIMARY KEY FOREIGN KEY
@coding_interview_preparation
⭐️ Behavioral: Nail Any “Tell Me About a Time” Question
Use STAR method (Amazon/Google favorite):
Situation: Short context
Task: Your responsibility
Action: What you did (focus here)
Result: Quantify outcome (numbers = gold)
Example Question:
❌ Bad: Ramble story.
✅Good: 60-sec STAR answer ending with “...resulted in 25% faster processing.”
👉 Pro Move: Prepare 3-4 stories (failure, leadership, teamwork, conflict). Practice out loud. End with what you learned.
This decides “culture fit”, prepare as hard as coding!
Use STAR method (Amazon/Google favorite):
Situation: Short context
Task: Your responsibility
Action: What you did (focus here)
Result: Quantify outcome (numbers = gold)
Example Question:
Tell me about a challenging project.
❌ Bad: Ramble story.
✅Good: 60-sec STAR answer ending with “...resulted in 25% faster processing.”
👉 Pro Move: Prepare 3-4 stories (failure, leadership, teamwork, conflict). Practice out loud. End with what you learned.
This decides “culture fit”, prepare as hard as coding!
❤3
HTTP status codes: Quick cheat sheet
✅ 200 OK: request succeeded
🆕 201 Created: new resource saved
📝 204 No Content: success, nothing to return
🔀 301 Moved Permanently: use new URL
↪️ 302 Found: temporary redirect
🧾 304 Not Modified: use cached version
🙅 400 Bad Request: invalid input
🪪 401 Unauthorized: missing/invalid auth
🚫 403 Forbidden: authenticated but not allowed
❓ 404 Not Found: resource doesn’t exist
⏳ 408 Request Timeout: client took too long
🧯 409 Conflict: state/version clash
💥 500 Internal Server Error: server crashed
🛠 502 Bad Gateway: upstream failed
🕸 503 Service Unavailable: overloaded/maintenance
⌛️ 504 Gateway Timeout: upstream too slow
✔️ Tips
• return precise codes; don’t default to 200/500
• include a machine-readable error body (code, message, details)
• never leak stack traces in production
• pair 304 with ETag/If-None-Match for caching
✅ 200 OK: request succeeded
🆕 201 Created: new resource saved
📝 204 No Content: success, nothing to return
🔀 301 Moved Permanently: use new URL
↪️ 302 Found: temporary redirect
🧾 304 Not Modified: use cached version
🙅 400 Bad Request: invalid input
🪪 401 Unauthorized: missing/invalid auth
🚫 403 Forbidden: authenticated but not allowed
❓ 404 Not Found: resource doesn’t exist
⏳ 408 Request Timeout: client took too long
🧯 409 Conflict: state/version clash
💥 500 Internal Server Error: server crashed
🛠 502 Bad Gateway: upstream failed
🕸 503 Service Unavailable: overloaded/maintenance
⌛️ 504 Gateway Timeout: upstream too slow
✔️ Tips
• return precise codes; don’t default to 200/500
• include a machine-readable error body (code, message, details)
• never leak stack traces in production
• pair 304 with ETag/If-None-Match for caching
❤2
🔄 Recursion & Backtracking Basics
Core Idea: Function calls itself to break big problems into smaller identical ones. Add backtracking to explore all possibilities and undo choices.
When to use: Subsets, permutations, combinations, or maze/path problems.
🗯Real Interview Scenario:
or “Word Search” in a grid.
✅ How to shine: Explain:
Draw the recursion tree verbally. Always define clear base case first. Watch stack depth for large inputs.
Practice 4-5 problems. Once comfortable, you’ll handle many medium/hard questions confidently.
Core Idea: Function calls itself to break big problems into smaller identical ones. Add backtracking to explore all possibilities and undo choices.
When to use: Subsets, permutations, combinations, or maze/path problems.
🗯Real Interview Scenario:
Generate all subsets
or “Word Search” in a grid.
✅ How to shine: Explain:
I’ll use recursion with backtracking to try choices and undo them.
Draw the recursion tree verbally. Always define clear base case first. Watch stack depth for large inputs.
Practice 4-5 problems. Once comfortable, you’ll handle many medium/hard questions confidently.
❤2
✅ DSA Roadmap for Coding Interviews 🧠
1️⃣ Start with the Basics
– Learn Time & Space Complexity
– Understand Big O notation
2️⃣ Master Arrays & Strings
– Sliding window, Two pointers, Prefix sum
– Practice problems like: Two Sum, Move Zeroes
3️⃣ Dive into Hashing
– Use HashMap/HashSet for fast lookups
– Problems: Longest Substring Without Repeat, Group Anagrams
4️⃣ Linked Lists
– Learn traversal, reversal, cycle detection
– Key problems: Detect Cycle, Merge Two Sorted Lists
5️⃣ Stacks & Queues
– Infix to postfix, parentheses validation, monotonic stack
– Problems: Valid Parentheses, Next Greater Element
6️⃣ Recursion & Backtracking
– Subsets, Permutations, N-Queens
– Key skill: build solution tree and backtrack correctly
7️⃣ Binary Search & Search Problems
– Classic problems: Search in Rotated Array, Koko Eating Bananas
– Understand upper/lower bounds
8️⃣ Trees & Binary Trees
– DFS, BFS, Inorder/Preorder/Postorder
– Problems: Lowest Common Ancestor, Diameter of Tree
9️⃣ Heaps & Priority Queues
– Top K elements, Min/Max heap use cases
🔟 Graphs
– BFS, DFS, Union-Find, Dijkstra’s
– Practice shortest path, connected components, cycle detection
1️⃣1️⃣ Dynamic Programming (DP)
– Start with 1D DP (Fibonacci, Climbing Stairs)
– Move to 2D DP (Knapsack, LCS, Grid Paths)
💡Practice on LeetCode, Codeforces, GFG. Use patterns, not memorization.
@coding_interview_preparation
1️⃣ Start with the Basics
– Learn Time & Space Complexity
– Understand Big O notation
2️⃣ Master Arrays & Strings
– Sliding window, Two pointers, Prefix sum
– Practice problems like: Two Sum, Move Zeroes
3️⃣ Dive into Hashing
– Use HashMap/HashSet for fast lookups
– Problems: Longest Substring Without Repeat, Group Anagrams
4️⃣ Linked Lists
– Learn traversal, reversal, cycle detection
– Key problems: Detect Cycle, Merge Two Sorted Lists
5️⃣ Stacks & Queues
– Infix to postfix, parentheses validation, monotonic stack
– Problems: Valid Parentheses, Next Greater Element
6️⃣ Recursion & Backtracking
– Subsets, Permutations, N-Queens
– Key skill: build solution tree and backtrack correctly
7️⃣ Binary Search & Search Problems
– Classic problems: Search in Rotated Array, Koko Eating Bananas
– Understand upper/lower bounds
8️⃣ Trees & Binary Trees
– DFS, BFS, Inorder/Preorder/Postorder
– Problems: Lowest Common Ancestor, Diameter of Tree
9️⃣ Heaps & Priority Queues
– Top K elements, Min/Max heap use cases
🔟 Graphs
– BFS, DFS, Union-Find, Dijkstra’s
– Practice shortest path, connected components, cycle detection
1️⃣1️⃣ Dynamic Programming (DP)
– Start with 1D DP (Fibonacci, Climbing Stairs)
– Move to 2D DP (Knapsack, LCS, Grid Paths)
💡Practice on LeetCode, Codeforces, GFG. Use patterns, not memorization.
@coding_interview_preparation
❤5
💰 Greedy Algorithm Mindset
📖 Core Idea: Greedy makes the locally best choice at every step, hoping these choices lead to a global optimum. It works well when the problem has optimal substructure and a greedy choice property that you can prove or justify.
🗯 Real Interview Scenario: “Jump Game”, “Minimum Number of Arrows to Burst Balloons”, or interval scheduling.
✅ How to shine: Share your greedy intuition first, then briefly prove why it works (e.g., “Sorting by end time guarantees we fit maximum activities”). Compare with DP when asked. This shows deeper problem-solving maturity.
📖 Core Idea: Greedy makes the locally best choice at every step, hoping these choices lead to a global optimum. It works well when the problem has optimal substructure and a greedy choice property that you can prove or justify.
🗯 Real Interview Scenario: “Jump Game”, “Minimum Number of Arrows to Burst Balloons”, or interval scheduling.
✅ How to shine: Share your greedy intuition first, then briefly prove why it works (e.g., “Sorting by end time guarantees we fit maximum activities”). Compare with DP when asked. This shows deeper problem-solving maturity.
❤2
💻 Backend Basics Interview Questions – (Node.js)
📍 1. What is Node.js?
Answer: Node.js is a runtime environment that lets you run JavaScript on the server side. It uses Google’s V8 engine and is designed for building scalable network applications.
📍 2. How is Node.js different from traditional server-side platforms?
Answer: Unlike PHP or Java, Node.js is event-driven and non-blocking. This makes it lightweight and efficient for I/O-heavy operations like APIs and real-time apps.
📍 3. What is the role of the package.json file?
Answer: It stores metadata about your project (name, version, scripts) and dependencies. It’s essential for managing and sharing Node.js projects.
📍 4. What are CommonJS modules in Node.js?
Answer: Node uses CommonJS to handle modules. You use require() to import and module.exports to export code between files.
📍 5. What is the Event Loop in Node.js?
Answer: It allows Node.js to handle many connections asynchronously without blocking. It’s the heart of Node’s non-blocking architecture.
📍 6. What is middleware in Node.js (Express)?
Answer: Middleware functions process requests before sending a response. They can be used for logging, auth, validation, etc.
📍 7. What is the difference between process.nextTick(), setTimeout(), and setImmediate()?
Answer:
⦁ process.nextTick() runs after the current operation, before the next event loop.
⦁ setTimeout() runs after a minimum delay.
⦁ setImmediate() runs on the next cycle of the event loop.
📍 8. What is a callback function in Node.js?
Answer: A function passed as an argument to another function, executed after an async task finishes. It’s the core of async programming in Node.
📍 9. What are Streams in Node.js?
Answer: Streams let you read/write data piece-by-piece (chunks), great for handling large files. Types: Readable, Writable, Duplex, Transform.
📍 10. What is the difference between require and import?
Answer:
⦁ require is CommonJS (used in Node.js by default).
⦁ import is ES6 module syntax (used with "type": "module" in package.json).
📍 1. What is Node.js?
Answer: Node.js is a runtime environment that lets you run JavaScript on the server side. It uses Google’s V8 engine and is designed for building scalable network applications.
📍 2. How is Node.js different from traditional server-side platforms?
Answer: Unlike PHP or Java, Node.js is event-driven and non-blocking. This makes it lightweight and efficient for I/O-heavy operations like APIs and real-time apps.
📍 3. What is the role of the package.json file?
Answer: It stores metadata about your project (name, version, scripts) and dependencies. It’s essential for managing and sharing Node.js projects.
📍 4. What are CommonJS modules in Node.js?
Answer: Node uses CommonJS to handle modules. You use require() to import and module.exports to export code between files.
📍 5. What is the Event Loop in Node.js?
Answer: It allows Node.js to handle many connections asynchronously without blocking. It’s the heart of Node’s non-blocking architecture.
📍 6. What is middleware in Node.js (Express)?
Answer: Middleware functions process requests before sending a response. They can be used for logging, auth, validation, etc.
📍 7. What is the difference between process.nextTick(), setTimeout(), and setImmediate()?
Answer:
⦁ process.nextTick() runs after the current operation, before the next event loop.
⦁ setTimeout() runs after a minimum delay.
⦁ setImmediate() runs on the next cycle of the event loop.
📍 8. What is a callback function in Node.js?
Answer: A function passed as an argument to another function, executed after an async task finishes. It’s the core of async programming in Node.
📍 9. What are Streams in Node.js?
Answer: Streams let you read/write data piece-by-piece (chunks), great for handling large files. Types: Readable, Writable, Duplex, Transform.
📍 10. What is the difference between require and import?
Answer:
⦁ require is CommonJS (used in Node.js by default).
⦁ import is ES6 module syntax (used with "type": "module" in package.json).
❤2
⏫ Monotonic Stack: Next Greater Element
📖 Core Idea: A monotonic stack keeps elements in strictly increasing or decreasing order. As you iterate, you pop elements that violate the order and use the popped results to answer “next greater/smaller” questions efficiently in a single pass.
🗯Real Interview Scenario: “Next Greater Element”, “Daily Temperatures”, or “Largest Rectangle in Histogram”.
✅ How to shine: Say:
Explain why you traverse right-to-left for next greater. Dry-run a small example out loud. Interviewers love this clarity.
📖 Core Idea: A monotonic stack keeps elements in strictly increasing or decreasing order. As you iterate, you pop elements that violate the order and use the popped results to answer “next greater/smaller” questions efficiently in a single pass.
🗯Real Interview Scenario: “Next Greater Element”, “Daily Temperatures”, or “Largest Rectangle in Histogram”.
✅ How to shine: Say:
I’ll maintain a monotonic decreasing stack of indices to find the first larger element in O(n) time
Explain why you traverse right-to-left for next greater. Dry-run a small example out loud. Interviewers love this clarity.
Hey, you probably saw in other channels that its my 31st birthday today 🥳
You also maybe saw that I have become a father, so I took vacation to be with my son 👼❤️ and also during this vacation I worked really hard while my boy sleeps to make our channels much more useful, so I am starting with this one.
Starting tomorrow this channel will prepare you for your job interviews. There will posts more often and all posts will be related to each other.
Get ready for coding challenges with hints and full solutions, quizzes that actually check what you learned, SQL and System Design series that build in difficulty week over week, plus real resources - not just tips to scroll past.
I hope you will find it useful,
your @bigdataspecialist 🧡
You also maybe saw that I have become a father, so I took vacation to be with my son 👼❤️ and also during this vacation I worked really hard while my boy sleeps to make our channels much more useful, so I am starting with this one.
Starting tomorrow this channel will prepare you for your job interviews. There will posts more often and all posts will be related to each other.
Get ready for coding challenges with hints and full solutions, quizzes that actually check what you learned, SQL and System Design series that build in difficulty week over week, plus real resources - not just tips to scroll past.
I hope you will find it useful,
your @bigdataspecialist 🧡
❤2
🚀 Welcome to the channel that actually gets you hired
Not another "10 tips to ace your interview" account.
Here you'll get:
🧠 Real interview questions (the ones companies actually ask)
🐛 Bugs that will make you say "oh no, I do that too"
💰 Salary scripts you can copy-paste into your next negotiation
🎯 Recruiter secrets nobody tells you
📊 SQL & System Design, from "what's a JOIN" to "design Netflix"
No fluff. No generic advice. Just the stuff that gets offers.
Drop a 🔥 if you're prepping for interviews right now - let's see how many of us are grinding together.
Not another "10 tips to ace your interview" account.
Here you'll get:
🧠 Real interview questions (the ones companies actually ask)
🐛 Bugs that will make you say "oh no, I do that too"
💰 Salary scripts you can copy-paste into your next negotiation
🎯 Recruiter secrets nobody tells you
📊 SQL & System Design, from "what's a JOIN" to "design Netflix"
No fluff. No generic advice. Just the stuff that gets offers.
Drop a 🔥 if you're prepping for interviews right now - let's see how many of us are grinding together.
🔥1
🎯 CODING CHALLENGE #1 - Two Sum
Difficulty: Easy | Asked at: Google, Amazon, Meta
Given an array of integers
You can't use the same element twice, and there's exactly one valid answer.
💡 Hint: Before you reach for a brute-force double loop, ask yourself - what if you could look up "have I seen the number I need?" in O(1)?
Try it yourself before scrolling for the solution 👇
Solution:
Complexity: O(n) time, O(n) space - one pass, hash map lookup.
Common mistake: Candidates often solve this with nested loops (O(n²)) and stop there. If you already have the optimal solution, say it out loud early: "I can brute-force this in O(n²), but I think we can do better with a hash map." That sentence alone signals seniority.
What's the first approach that came to your mind? 🤔
Difficulty: Easy | Asked at: Google, Amazon, Meta
Given an array of integers
nums and a target, return the indices of the two numbers that add up to target.python
nums = [2, 7, 11, 15]
target = 9
# Expected output: [0, 1]
You can't use the same element twice, and there's exactly one valid answer.
💡 Hint: Before you reach for a brute-force double loop, ask yourself - what if you could look up "have I seen the number I need?" in O(1)?
Try it yourself before scrolling for the solution 👇
Solution:
python
def two_sum(nums, target):
seen = {}
for i, num in enumerate(nums):
complement = target - num
if complement in seen:
return [seen[complement], i]
seen[num] = i
return []
Complexity: O(n) time, O(n) space - one pass, hash map lookup.
Common mistake: Candidates often solve this with nested loops (O(n²)) and stop there. If you already have the optimal solution, say it out loud early: "I can brute-force this in O(n²), but I think we can do better with a hash map." That sentence alone signals seniority.
What's the first approach that came to your mind? 🤔
🔍 GUESS THE OUTPUT #1
Language: JavaScript
Lock in your answer, then vote on the quiz below 👇
Language: JavaScript
javascript
console.log(0.1 + 0.2 === 0.3);
console.log([1, 2, 3] + [4, 5, 6]);
console.log(typeof NaN);
Lock in your answer, then vote on the quiz below 👇
❤1
🔍 GUESS THE OUTPUT #1 - full breakdown
We apologize for marking wrong answe as correct in previous question. Explanation was correct, but right answer was not marked properly by accident.
Correct answer is false.
Here are some additional ones.
Answers:
1️⃣
2️⃣
3️⃣
Got all 3 right? Drop a ✅
Missed one? Drop the number you got wrong - let's talk about it.
We apologize for marking wrong answe as correct in previous question. Explanation was correct, but right answer was not marked properly by accident.
Correct answer is false.
Here are some additional ones.
javascript
console.log(0.1 + 0.2 === 0.3);
console.log([1, 2, 3] + [4, 5, 6]);
console.log(typeof NaN);
Answers:
1️⃣
false - floating point math isn't exact. 0.1 + 0.2 = 0.300000000000000042️⃣
"1,2,34,5,6" - arrays get coerced to strings and concatenated, not added3️⃣
"number" - yes, NaN is technically a number type. Ironic, we know.Got all 3 right? Drop a ✅
Missed one? Drop the number you got wrong - let's talk about it.
📊 SQL SATURDAY #1 - The Basics, Done Right
Let's start simple but do it properly. Here's our table:
Question: Find all employees in Engineering earning more than 100,000.
Simple, right? But here's the interview trap:
⚠️ Common pitfall: People forget
Fix it by repeating the expression or using a subquery/CTE. We'll get into CTEs in a few weeks 👀
What's a SQL mistake that tripped you up early on? 😅
Let's start simple but do it properly. Here's our table:
employees
+----+----------+------------+--------+
| id | name | department | salary |
+----+----------+------------+--------+
| 1 | Alice | Engineering| 95000 |
| 2 | Bob | Sales | 62000 |
| 3 | Charlie | Engineering| 105000 |
| 4 | Diana | Marketing | 70000 |
+----+----------+------------+--------+
Question: Find all employees in Engineering earning more than 100,000.
sql
SELECT name, salary
FROM employees
WHERE department = 'Engineering'
AND salary > 100000;
Simple, right? But here's the interview trap:
⚠️ Common pitfall: People forget
WHERE runs before SELECT logically, so you can't reference a column alias defined in SELECT inside your WHERE clause.sql
-- This will ERROR in most databases:
SELECT salary * 1.1 AS new_salary
FROM employees
WHERE new_salary > 100000; -- ❌ new_salary doesn't exist yet here
Fix it by repeating the expression or using a subquery/CTE. We'll get into CTEs in a few weeks 👀
What's a SQL mistake that tripped you up early on? 😅
❤6
🕵️ RECRUITER SECRETS #1
Here's something most candidates don't know:
Recruiters usually decide whether to move you forward within the first 30 seconds of reading your resume.
Not because they're lazy - because they're screening 200+ resumes for one role and pattern-matching fast.
What they scan for first:
✅ Job titles that match seniority level
✅ Tech stack keywords from the job description
✅ Quantified impact ("reduced load time by 40%" > "worked on performance")
✅ No unexplained gaps or job-hopping without context
What kills your chances instantly:
❌ A generic objective statement nobody reads
❌ Walls of text with no visual hierarchy
❌ Listing responsibilities instead of outcomes
Pro tip: Tailor your top 3 bullet points to mirror the exact language in the job posting. ATS systems and human recruiters both respond to it.
Has a recruiter ever given you feedback on your resume? Share it below 👇
Here's something most candidates don't know:
Recruiters usually decide whether to move you forward within the first 30 seconds of reading your resume.
Not because they're lazy - because they're screening 200+ resumes for one role and pattern-matching fast.
What they scan for first:
✅ Job titles that match seniority level
✅ Tech stack keywords from the job description
✅ Quantified impact ("reduced load time by 40%" > "worked on performance")
✅ No unexplained gaps or job-hopping without context
What kills your chances instantly:
❌ A generic objective statement nobody reads
❌ Walls of text with no visual hierarchy
❌ Listing responsibilities instead of outcomes
Pro tip: Tailor your top 3 bullet points to mirror the exact language in the job posting. ATS systems and human recruiters both respond to it.
Has a recruiter ever given you feedback on your resume? Share it below 👇
❤3
🧠 EDUCATIONAL CS #1 - Big O, Explained Without the Jargon
Big O isn't about "how fast is my code." It's about "how does my code's cost grow as the input grows."
Think of it like this:
📦 O(1) - Grabbing the first item in a box. Doesn't matter if the box has 10 or 10 million items.
📦 O(log n) - Finding a word in a dictionary by flipping to the middle, then the middle of that half, and so on. Doubling the dictionary size only adds one more flip.
📦 O(n) - Reading every page of a book once. Twice the pages, twice the time.
📦 O(n log n) - Sorting a deck of cards efficiently (merge sort). A bit worse than linear, way better than...
📦 O(n²) - Comparing every card in the deck to every other card. Double the deck, quadruple the work.
Here's the part interviewers actually care about: can you identify the complexity of code you didn't write, and can you explain why, not just state the label.
Quick check - what's the time complexity of this?
Drop your answer below 👇 (hint: it's not quite O(n²))
Big O isn't about "how fast is my code." It's about "how does my code's cost grow as the input grows."
Think of it like this:
📦 O(1) - Grabbing the first item in a box. Doesn't matter if the box has 10 or 10 million items.
📦 O(log n) - Finding a word in a dictionary by flipping to the middle, then the middle of that half, and so on. Doubling the dictionary size only adds one more flip.
📦 O(n) - Reading every page of a book once. Twice the pages, twice the time.
📦 O(n log n) - Sorting a deck of cards efficiently (merge sort). A bit worse than linear, way better than...
📦 O(n²) - Comparing every card in the deck to every other card. Double the deck, quadruple the work.
Here's the part interviewers actually care about: can you identify the complexity of code you didn't write, and can you explain why, not just state the label.
Quick check - what's the time complexity of this?
python
def mystery(arr):
for i in range(len(arr)):
for j in range(i, len(arr)):
print(arr[i], arr[j])
Drop your answer below 👇 (hint: it's not quite O(n²))
🧠 7 Golden Rules to Crack Data Science Interviews 🧑💻
1️⃣ Master the Fundamentals
⦁ Be clear on stats, ML algorithms, and probability
⦁ Brush up on SQL, Python, and data wrangling
2️⃣ Know Your Projects Deeply
⦁ Be ready to explain models, metrics, and business impact
⦁ Prepare for follow-up questions
3️⃣ Practice Case Studies & Product Thinking
⦁ Think beyond code - focus on solving real problems
⦁ Show how your solution helps the business
4️⃣ Explain Trade-offs
⦁ Why Random Forest vs. XGBoost?
⦁ Discuss bias-variance, precision-recall, etc.
5️⃣ Be Confident with Metrics
⦁ Accuracy isn’t enough - explain F1-score, ROC, AUC
⦁ Tie metrics to the business goal
6️⃣ Ask Clarifying Questions
⦁ Never rush into an answer
⦁ Clarify objective, constraints, and assumptions
7️⃣ Stay Updated & Curious
⦁ Follow latest tools (like LangChain, LLMs)
⦁ Share your learning journey on GitHub or blogs
@coding_interview_preparation
1️⃣ Master the Fundamentals
⦁ Be clear on stats, ML algorithms, and probability
⦁ Brush up on SQL, Python, and data wrangling
2️⃣ Know Your Projects Deeply
⦁ Be ready to explain models, metrics, and business impact
⦁ Prepare for follow-up questions
3️⃣ Practice Case Studies & Product Thinking
⦁ Think beyond code - focus on solving real problems
⦁ Show how your solution helps the business
4️⃣ Explain Trade-offs
⦁ Why Random Forest vs. XGBoost?
⦁ Discuss bias-variance, precision-recall, etc.
5️⃣ Be Confident with Metrics
⦁ Accuracy isn’t enough - explain F1-score, ROC, AUC
⦁ Tie metrics to the business goal
6️⃣ Ask Clarifying Questions
⦁ Never rush into an answer
⦁ Clarify objective, constraints, and assumptions
7️⃣ Stay Updated & Curious
⦁ Follow latest tools (like LangChain, LLMs)
⦁ Share your learning journey on GitHub or blogs
@coding_interview_preparation
❤2
Forwarded from Cool GitHub repositories
💼 20 GitHub Repositories to Help You Get Hired
1. coding-interview-university
A complete self-study roadmap originally created to prepare for Google software engineering interviews.
2. awesome-interview-questions
A curated collection of technical interview questions across dozens of programming languages and technologies.
3. system-design-primer
One of the best resources for mastering system design interviews at top tech companies.
4. build-your-own-x
Learn by building your own database, operating system, Git, Docker, Redis, and dozens of other technologies.
5. developer-roadmap
Interactive roadmaps showing exactly what to learn for frontend, backend, DevOps, AI, cybersecurity, and more.
6. project-based-learning
Learn programming by building real projects instead of following endless tutorials.
7. app-ideas
Hundreds of project ideas ranging from beginner to advanced to strengthen your portfolio.
8. public-apis
A massive collection of free APIs you can use to build real-world portfolio projects.
9. free-programming-books
Thousands of free programming books, courses, and learning resources in multiple languages.
10. first-contributions
A step-by-step guide that teaches you how to make your first pull request.
11. frontend-practice
Practice rebuilding real company websites to improve your frontend development skills.
12. Frontend Mentor Challenges
Realistic UI challenges that help you build an employer-ready frontend portfolio.
13. awesome-resume
A professional, ATS-friendly resume template widely used by software engineers.
14. The Algorithms
A huge collection of algorithms and data structures implemented in dozens of programming languages.
15. Tech Interview Handbook
Covers coding interviews, behavioral interviews, resume tips, salary negotiation, and more.
16. awesome
The original Awesome list containing thousands of carefully curated developer resources.
17. realworld
Build the same production-grade application in different frameworks to learn industry architecture.
18. awesome-for-beginners
Find beginner-friendly open source projects to make your first GitHub contributions.
19. awesome-cheatsheets
A collection of programming and DevOps cheat sheets for quick reference during development.
20. Awesome Job Boards
A curated collection of the best tech job boards, including remote, startup, and developer-focused hiring platforms.
💻Master these repositories, build projects from them, contribute to open source, and you'll have both the skills and portfolio that recruiters actually look for.
1. coding-interview-university
A complete self-study roadmap originally created to prepare for Google software engineering interviews.
2. awesome-interview-questions
A curated collection of technical interview questions across dozens of programming languages and technologies.
3. system-design-primer
One of the best resources for mastering system design interviews at top tech companies.
4. build-your-own-x
Learn by building your own database, operating system, Git, Docker, Redis, and dozens of other technologies.
5. developer-roadmap
Interactive roadmaps showing exactly what to learn for frontend, backend, DevOps, AI, cybersecurity, and more.
6. project-based-learning
Learn programming by building real projects instead of following endless tutorials.
7. app-ideas
Hundreds of project ideas ranging from beginner to advanced to strengthen your portfolio.
8. public-apis
A massive collection of free APIs you can use to build real-world portfolio projects.
9. free-programming-books
Thousands of free programming books, courses, and learning resources in multiple languages.
10. first-contributions
A step-by-step guide that teaches you how to make your first pull request.
11. frontend-practice
Practice rebuilding real company websites to improve your frontend development skills.
12. Frontend Mentor Challenges
Realistic UI challenges that help you build an employer-ready frontend portfolio.
13. awesome-resume
A professional, ATS-friendly resume template widely used by software engineers.
14. The Algorithms
A huge collection of algorithms and data structures implemented in dozens of programming languages.
15. Tech Interview Handbook
Covers coding interviews, behavioral interviews, resume tips, salary negotiation, and more.
16. awesome
The original Awesome list containing thousands of carefully curated developer resources.
17. realworld
Build the same production-grade application in different frameworks to learn industry architecture.
18. awesome-for-beginners
Find beginner-friendly open source projects to make your first GitHub contributions.
19. awesome-cheatsheets
A collection of programming and DevOps cheat sheets for quick reference during development.
20. Awesome Job Boards
A curated collection of the best tech job boards, including remote, startup, and developer-focused hiring platforms.
💻Master these repositories, build projects from them, contribute to open source, and you'll have both the skills and portfolio that recruiters actually look for.
❤3