Coding Interview Resources

✅ Coding Basics You Should Know 👨‍💻

If you're starting your journey in programming, here are the core concepts every beginner must understand:

1️⃣ What is Coding?
Coding is writing instructions a computer can understand. These instructions are written using programming languages like Python, JavaScript, C++, etc.

2️⃣ Programming Languages
• Python – Beginner-friendly, great for automation, AI
• JavaScript – For web interactivity
• C++ / Java – Used in competitive programming system development
Each language has syntax, variables, functions, and logic flow.

3️⃣ Variables Data Types
Used to store information.
name = "Alice" # string
age = 25 # integer

4️⃣ Conditions Loops
Code decisions and repetitions.
if age > 18:
print("Adult")

for i in range(5):
print(i)

5️⃣ Functions
Reusable blocks of code.
def greet(name):
return f"Hello, {name}"

6️⃣ Data Structures
Used to organize and manage data:
• Lists / Arrays
• Dictionaries / Maps
• Stacks Queues
• Sets

7️⃣ Problem Solving (DSA)
Learn to break problems into steps using:
• Algorithms (search, sort)
• Logic patterns
• Code efficiency (time/space complexity)

8️⃣ Debugging
The skill of finding and fixing bugs using:
• Print statements
• Debug tools in IDEs (like VS Code or PyCharm)

9️⃣ Git GitHub
Version control and collaboration.
git init
git add .
git commit -m "Initial code"

🔟 Build Projects
Start with small apps like:
• Calculator
• To-Do List
• Weather App
• Portfolio Website

💡 Coding is best learned by doing. Practice daily, build real projects, and challenge yourself with problems on platforms like LeetCode, HackerRank, and Codewars.

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Coding Interview Resources

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Coding Interview Resources

SQL Cheat Sheet for Data Analysts 🗄️📊

1. SELECT
What it is: Used to choose columns from a table
What it does: Returns specific columns of data

Query: Fetch name and salary

SELECT name, salary 
FROM employees;

2. FROM
What it is: Specifies the table
What it does: Tells SQL where to get data from

Query: Fetch all data from employees

SELECT * 
FROM employees;

3. WHERE
What it is: Filters rows based on condition
What it does: Returns only matching rows

Query: Employees with salary > 30000

SELECT * 
FROM employees 
WHERE salary > 30000;

4. ORDER BY
What it is: Sorts the data
What it does: Arranges rows in order

Query: Sort by salary (highest first)

SELECT * 
FROM employees 
ORDER BY salary DESC;

5. COUNT()
What it is: Counts rows
What it does: Returns total records

Query: Count employees

SELECT COUNT(*) 
FROM employees;

6. AVG()
What it is: Calculates average
What it does: Returns mean value

Query: Average salary

SELECT AVG(salary) 
FROM employees;

7. GROUP BY
What it is: Groups rows by column
What it does: Applies aggregation per group

Query: Avg salary per department

SELECT department, AVG(salary) 
FROM employees 
GROUP BY department;

8. HAVING
What it is: Filters grouped data
What it does: Returns filtered groups

Query: Departments with avg salary > 40000

SELECT department, AVG(salary) 
FROM employees 
GROUP BY department 
HAVING AVG(salary) > 40000;

9. INNER JOIN
What it is: Combines matching rows from tables
What it does: Returns common data

Query: Employees with department names

SELECT e.name, d.department_name 
FROM employees e 
INNER JOIN departments d 
ON e.dept_id = d.dept_id;

10. LEFT JOIN
What it is: Combines all left + matching right
What it does: Returns all left table data

Query: All employees with departments

SELECT e.name, d.department_name 
FROM employees e 
LEFT JOIN departments d 
ON e.dept_id = d.dept_id;

11. CASE WHEN
What it is: Conditional logic
What it does: Creates values based on condition

Query: Categorize salary

SELECT name, 
    CASE 
        WHEN salary > 40000 THEN 'High' 
        ELSE 'Low' 
    END AS category 
FROM employees;

12. SUBQUERY
What it is: Query inside another query
What it does: Uses result of inner query

Query: Salary above average

SELECT name, salary 
FROM employees 
WHERE salary > ( 
    SELECT AVG(salary) 
    FROM employees 
);

13. RANK()
What it is: Window function
What it does: Assigns rank without grouping

Query: Rank employees by salary

SELECT name, salary, 
    RANK() OVER (ORDER BY salary DESC) AS rank 
FROM employees;

14. DISTINCT
What it is: Removes duplicates
What it does: Returns unique values

Query: Unique departments

SELECT DISTINCT department 
FROM employees;

15. LIKE
What it is: Pattern matching
What it does: Filters text patterns

Query: Names starting with A

SELECT * 
FROM employees 
WHERE name LIKE 'A%';

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Coding Interview Resources

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982 views12:25

Coding Interview Resources

Top interview SQL questions, including both technical and non-technical questions, along with their answers PART-1

1. What is SQL?
   - Answer: SQL (Structured Query Language) is a standard programming language specifically designed for managing and manipulating relational databases.

2. What are the different types of SQL statements?
   - Answer: SQL statements can be classified into DDL (Data Definition Language), DML (Data Manipulation Language), DCL (Data Control Language), and TCL (Transaction Control Language).

3. What is a primary key?
   - Answer: A primary key is a field (or combination of fields) in a table that uniquely identifies each row/record in that table.

4. What is a foreign key?
   - Answer: A foreign key is a field (or collection of fields) in one table that uniquely identifies a row of another table or the same table. It establishes a link between the data in two tables.

5. What are joins? Explain different types of joins.
   - Answer: A join is an SQL operation for combining records from two or more tables. Types of joins include INNER JOIN, LEFT JOIN (or LEFT OUTER JOIN), RIGHT JOIN (or RIGHT OUTER JOIN), and FULL JOIN (or FULL OUTER JOIN).

6. What is normalization?
   - Answer: Normalization is the process of organizing data to reduce redundancy and improve data integrity. This typically involves dividing a database into two or more tables and defining relationships between them.

7. What is denormalization?
   - Answer: Denormalization is the process of combining normalized tables into fewer tables to improve database read performance, sometimes at the expense of write performance and data integrity.

8. What is stored procedure?
   - Answer: A stored procedure is a prepared SQL code that you can save and reuse. So, if you have an SQL query that you write frequently, you can save it as a stored procedure and then call it to execute it.

9. What is an index?
   - Answer: An index is a database object that improves the speed of data retrieval operations on a table at the cost of additional storage and maintenance overhead.

10. What is a view in SQL?
    - Answer: A view is a virtual table based on the result set of an SQL query. It contains rows and columns, just like a real table, but does not physically store the data.

11. What is a subquery?
    - Answer: A subquery is an SQL query nested inside a larger query. It is used to return data that will be used in the main query as a condition to further restrict the data to be retrieved.

12. What are aggregate functions in SQL?
    - Answer: Aggregate functions perform a calculation on a set of values and return a single value. Examples include COUNT, SUM, AVG (average), MIN (minimum), and MAX (maximum).

13. Difference between DELETE and TRUNCATE?
    - Answer: DELETE removes rows one at a time and logs each delete, while TRUNCATE removes all rows in a table without logging individual row deletions. TRUNCATE is faster but cannot be rolled back.

14. What is a UNION in SQL?
    - Answer: UNION is an operator used to combine the result sets of two or more SELECT statements. It removes duplicate rows between the various SELECT statements.

15. What is a cursor in SQL?
    - Answer: A cursor is a database object used to retrieve, manipulate, and navigate through a result set one row at a time.

16. What is trigger in SQL?
    - Answer: A trigger is a set of SQL statements that automatically execute or "trigger" when certain events occur in a database, such as INSERT, UPDATE, or DELETE.

17. Difference between clustered and non-clustered indexes?
    - Answer: A clustered index determines the physical order of data in a table and can only be one per table. A non-clustered index, on the other hand, creates a logical order and can be many per table.

18. Explain the term ACID.
    - Answer: ACID stands for Atomicity, Consistency, Isolation, and Durability.

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Coding Interview Resources

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Coding Interview Resources

Top 100 Coding Interview Questions

🧠 Data Structures & Algorithms (DSA)

1. What is an array and how is it stored in memory?
2. What is the difference between an array and a linked list?
3. Explain time complexity using Big‑O notation.
4. How do you implement a stack using an array?
5. How do you implement a queue using an array or linked list?
6. How does a hash table work?
7. How do you handle collisions in a hash table?
8. What is a binary tree and a binary search tree (BST)?
9. How do you traverse a tree (inorder, preorder, postorder)?
10. What is recursion and when is it useful?

🌱 Arrays, Strings, Two‑Pointers

11. How do you remove duplicates from a sorted array?
12. How do you solve “Two Sum” efficiently?
13. How do you reverse a string or array?
14. How do you find the maximum subarray sum (Kadane’s algorithm)?
15. How do you rotate an array?
16. How do you find the first missing positive number?
17. How do you implement sliding‑window problems?
18. How do you merge two sorted arrays?
19. How do you find the longest substring without repeating characters?
20. How do you implement a circular buffer?

🔗 Linked Lists

21. How do you reverse a singly linked list?
22. How do you detect a cycle in a linked list?
23. How do you find the middle node of a linked list?
24. How do you merge two sorted linked lists?
25. How do you find and remove a duplicate in a list?
26. How do you implement a dummy head in linked‑list problems?
27. How do you delete a node given only that node (no head)?
28. How do you implement a circular linked list?
29. How do you split a list into equal parts?
30. How do you implement a doubly linked list?

🗂️ Stacks, Queues, and Heaps

31. How do you implement a stack with a max‑stack (O(1) max query)?
32. How do you implement a queue using two stacks?
33. How do you design a stack that supports getMin() in O(1)?
34. What is a monotonic stack and when is it useful?
35. How do you implement a priority queue / heap?
36. How do you find the top K frequent elements?
37. How do you merge K sorted lists?
38. How do you implement LRU / LFU cache?
39. How do you check for balanced parentheses?
40. How do you implement a circular queue?

🌳 Trees & Graphs

41. How do you implement BFS and DFS on a graph?
42. How do you find the height / depth of a tree?
43. How do you implement level‑order traversal?
44. How do you check if a binary tree is a BST?
45. How do you implement preorder traversal iteratively?
46. How do you implement postorder traversal iteratively?
47. How do you find the lowest common ancestor (LCA)?
48. How do you serialize and deserialize a binary tree?
49. How do you detect a cycle in an undirected graph?
50. How do you implement Dijkstra’s algorithm?

📊 Sorting, Searching & DP

51. How do you implement quicksort and mergesort?
52. How do you implement binary search in a rotated sorted array?
53. How do you implement insertion sort and when is it useful?
54. How do you find the k‑th largest element?
55. What is the difference between DFS and backtracking?
56. How do you solve the “n‑queens” problem?
57. How do you generate subsets / permutations?
58. How do you solve coin‑change / unbounded‑knapsack?
59. How do you compute Fibonacci efficiently (DP vs matrix exponentiation)?
60. How do you implement longest increasing subsequence (LIS)?

🌐 Full‑Stack / System‑Design‑Style (General)

61. Explain how a web request travels from browser to server and back.
62. What is the difference between HTTP and HTTPS?
63. What is DNS and how does it work?
64. What is the role of a CDN?
65. How do you reduce latency in a web application?
66. What is caching and where do you place it?
67. What is the difference between horizontal and vertical scaling?
68. What is load balancing and how does it work?
69. What is rate limiting and how do you implement it?
70. How do you design a URL shortener system?

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1.06K viewsedited 19:08

Coding Interview Resources

📂 Databases & Backend Theory

71. What is the difference between SQL and NoSQL?
72. What is ACID and where is it important?
73. What is normalization and denormalization?
74. What is indexing and when is it useful?
75. What is sharding vs replication?
76. What is the difference between strong and eventual consistency?
77. What is a transaction and when do you roll it back?
78. What is connection pooling?
79. What is the CAP theorem?
80. How do you design a scalable schema for user‑generated content?

💡 Coding & Problem‑Pattern Practice

81. Write a function to find the sum of all elements in an array.
82. Write a function to reverse a string.
83. Write a function to find the longest palindromic substring.
84. Write a function to implement debounce.
85. Write a function to implement throttle.
86. Write a function to flatten a nested array.
87. Write a function to implement a simple pub/sub pattern.
88. Write a function to implement basic Promise.all.
89. Write a function to group anagrams.
90. Write a function to implement a simple LRU cache.

🧠 Behavioral & System‑Design (Full‑Stack / SWE)

91. Walk me through a project you built end‑to‑end.
92. Describe a time you exceeded performance / scalability requirements.
93. Tell me about a time you debugged a production bug.
94. Tell me about a time you reduced technical debt in a codebase.
95. How do you design a simple chat / notification system?
96. How would you design a file‑uploading service?
97. How would you design a task‑management / kanban app?
98. How do you collaborate between frontend and backend teams?
99. How do you handle conflicting requirements from product and infra?
100. How do you prepare yourself for system‑design interviews?

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Coding Interview Resources

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Coding Interview Resources

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Coding Interview Resources

Skills to master as a web developer

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Coding Interview Resources

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Coding Interview Resources

Top 100 Data Science Interview Questions ✅

Data Science Basics
1. What is data science and how is it different from data analytics?
2. What are the key steps in a data science lifecycle?
3. What types of problems does data science solve?
4. What skills does a data scientist need in real projects?
5. What is the difference between structured and unstructured data?
6. What is exploratory data analysis and why do you do it first?
7. What are common data sources in real companies?
8. What is feature engineering?
9. What is the difference between supervised and unsupervised learning?
10. What is bias in data and how does it affect models?

Statistics and Probability
11. What is the difference between mean, median, and mode?
12. What is standard deviation and variance?
13. What is probability distribution?
14. What is normal distribution and where is it used?
15. What is skewness and kurtosis?
16. What is correlation vs causation?
17. What is hypothesis testing?
18. What are Type I and Type II errors?
19. What is p-value?
20. What is confidence interval?

Data Cleaning and Preprocessing
21. How do you handle missing values?
22. How do you treat outliers?
23. What is data normalization and standardization?
24. When do you use Min-Max scaling vs Z-score?
25. How do you handle imbalanced datasets?
26. What is one-hot encoding?
27. What is label encoding?
28. How do you detect data leakage?
29. What is duplicate data and how do you handle it?
30. How do you validate data quality?

Python for Data Science
31. Why is Python popular in data science?
32. Difference between list, tuple, set, and dictionary?
33. What is NumPy and why is it fast?
34. What is Pandas and where do you use it?
35. Difference between loc and iloc?
36. What are vectorized operations?
37. What is lambda function?
38. What is list comprehension?
39. How do you handle large datasets in Python?
40. What are common Python libraries used in data science?

Data Visualization
41. Why is data visualization important?
42. Difference between bar chart and histogram?
43. When do you use box plots?
44. What does a scatter plot show?
45. What are common mistakes in data visualization?
46. Difference between Seaborn and Matplotlib?
47. What is a heatmap used for?
48. How do you visualize distributions?
49. What is dashboarding?
50. How do you choose the right chart?

Machine Learning Basics
51. What is machine learning?
52. Difference between regression and classification?
53. What is overfitting and underfitting?
54. What is train-test split?
55. What is cross-validation?
56. What is bias-variance tradeoff?
57. What is feature selection?
58. What is model evaluation?
59. What is baseline model?
60. How do you choose a model?

Supervised Learning
61. How does linear regression work?
62. Assumptions of linear regression?
63. What is logistic regression?
64. What is decision tree?
65. What is random forest?
66. What is KNN and when do you use it?
67. What is SVM?
68. How does Naive Bayes work?
69. What are ensemble methods?
70. How do you tune hyperparameters?

Unsupervised Learning
71. What is clustering?
72. Difference between K-means and hierarchical clustering?
73. How do you choose value of K?
74. What is PCA?
75. Why is dimensionality reduction needed?
76. What is anomaly detection?
77. What is association rule mining?
78. What is DBSCAN?
79. What is cosine similarity?
80. Where is unsupervised learning used?

Model Evaluation Metrics
81. What is accuracy and when is it misleading?
82. What is precision and recall?
83. What is F1 score?
84. What is ROC curve?
85. What is AUC?
86. Difference between confusion matrix metrics?
87. What is log loss?
88. What is RMSE?
89. What metric do you use for imbalanced data?
90. How do business metrics link to ML metrics?

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Coding Interview Resources

Deployment and Real-World Practice
91. What is model deployment?
92. What is batch vs real-time prediction?
93. What is model drift?
94. How do you monitor model performance?
95. What is feature store?
96. What is experiment tracking?
97. How do you explain model predictions?
98. What is data versioning?
99. How do you handle failed models?
100. How do you communicate results to non-technical stakeholders?

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Coding Interview Resources

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