๐ Top Coding Interview Concepts โ Part 2 ๐ป
11. Stack
A linear data structure that follows the LIFO (Last In, First Out) principle. The last element added is the first one removed.
12. Queue
A linear data structure that follows the FIFO (First In, First Out) principle. The first element added is the first one removed.
13. Hash Table (Hash Map)
A data structure that stores key-value pairs and provides fast insertion, deletion, and lookup using a hash function.
14. Tree
A hierarchical data structure consisting of nodes connected by edges, commonly used to represent hierarchical relationships.
15. Binary Search Tree (BST)
A special type of binary tree where values smaller than the root are stored on the left, and larger values on the right.
16. Graph
A collection of nodes (vertices) connected by edges, used to model relationships such as social networks or maps.
17. Sorting
The process of arranging data in a specific order, such as ascending or descending, to improve searching and processing.
18. Searching
The process of finding a specific element within a collection of data using algorithms like Linear Search or Binary Search.
19. Time Complexity
A measure of how the execution time of an algorithm grows as the input size increases, commonly represented using Big-O notation.
20. Space Complexity
A measure of the amount of memory an algorithm requires relative to the input size, helping evaluate memory efficiency.
๐ฌ Double Tap โค๏ธ for Part 3!
11. Stack
A linear data structure that follows the LIFO (Last In, First Out) principle. The last element added is the first one removed.
12. Queue
A linear data structure that follows the FIFO (First In, First Out) principle. The first element added is the first one removed.
13. Hash Table (Hash Map)
A data structure that stores key-value pairs and provides fast insertion, deletion, and lookup using a hash function.
14. Tree
A hierarchical data structure consisting of nodes connected by edges, commonly used to represent hierarchical relationships.
15. Binary Search Tree (BST)
A special type of binary tree where values smaller than the root are stored on the left, and larger values on the right.
16. Graph
A collection of nodes (vertices) connected by edges, used to model relationships such as social networks or maps.
17. Sorting
The process of arranging data in a specific order, such as ascending or descending, to improve searching and processing.
18. Searching
The process of finding a specific element within a collection of data using algorithms like Linear Search or Binary Search.
19. Time Complexity
A measure of how the execution time of an algorithm grows as the input size increases, commonly represented using Big-O notation.
20. Space Complexity
A measure of the amount of memory an algorithm requires relative to the input size, helping evaluate memory efficiency.
๐ฌ Double Tap โค๏ธ for Part 3!
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๐ง STEP 1: Learn SQL Basics
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๐ Databases to Practice:
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๐ STEP 2: Learn Filtering & Aggregation
โ DISTINCT
โ LIMIT & TOP
โ COUNT, SUM, AVG
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โก STEP 3: Master SQL JOINS
โ INNER JOIN
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๐ Concepts to Learn:
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โ Subqueries
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โ UNION & UNION ALL
โ EXISTS & IN
๐ฅ STEP 5: Learn Window Functions
โ ROW_NUMBER()
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โ DENSE_RANK()
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โ PARTITION BY
๐ง STEP 6: Learn Database Design
โ Normalization
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โ Query Optimization
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โ What is SQL?
โ Databases & Tables
โ SELECT Statement
โ WHERE Clause
โ ORDER BY
๐ Databases to Practice:
โ MySQL
โ PostgreSQL
โ SQL Server
๐ STEP 2: Learn Filtering & Aggregation
โ DISTINCT
โ LIMIT & TOP
โ COUNT, SUM, AVG
โ MIN & MAX
โ GROUP BY & HAVING
โก STEP 3: Master SQL JOINS
โ INNER JOIN
โ LEFT JOIN
โ RIGHT JOIN
โ FULL JOIN
โ SELF JOIN
๐ Concepts to Learn:
โ Primary Key
โ Foreign Key
โ Relationships
๐ STEP 4: Learn Advanced SQL
โ Subqueries
โ Common Table Expressions (CTEs)
โ CASE WHEN
โ UNION & UNION ALL
โ EXISTS & IN
๐ฅ STEP 5: Learn Window Functions
โ ROW_NUMBER()
โ RANK()
โ DENSE_RANK()
โ LEAD() & LAG()
โ PARTITION BY
๐ง STEP 6: Learn Database Design
โ Normalization
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