DSA (Data Structures and Algorithms) Essential Topics for Interviews

1️⃣ Arrays and Strings

Basic operations (insert, delete, update)

Two-pointer technique

Sliding window

Prefix sum

Kadane’s algorithm

Subarray problems


2️⃣ Linked List

Singly & Doubly Linked List

Reverse a linked list

Detect loop (Floyd’s Cycle)

Merge two sorted lists

Intersection of linked lists


3️⃣ Stack & Queue

Stack using array or linked list

Queue and Circular Queue

Monotonic Stack/Queue

LRU Cache (LinkedHashMap/Deque)

Infix to Postfix conversion


4️⃣ Hashing

HashMap, HashSet

Frequency counting

Two Sum problem

Group Anagrams

Longest Consecutive Sequence


5️⃣ Recursion & Backtracking

Base cases and recursive calls

Subsets, permutations

N-Queens problem

Sudoku solver

Word search


6️⃣ Trees & Binary Trees

Traversals (Inorder, Preorder, Postorder)

Height and Diameter

Balanced Binary Tree

Lowest Common Ancestor (LCA)

Serialize & Deserialize Tree


7️⃣ Binary Search Trees (BST)

Search, Insert, Delete

Validate BST

Kth smallest/largest element

Convert BST to DLL


8️⃣ Heaps & Priority Queues

Min Heap / Max Heap

Heapify

Top K elements

Merge K sorted lists

Median in a stream


9️⃣ Graphs

Representations (adjacency list/matrix)

DFS, BFS

Cycle detection (directed & undirected)

Topological Sort

Dijkstra’s & Bellman-Ford algorithm

Union-Find (Disjoint Set)


10️⃣ Dynamic Programming (DP)

0/1 Knapsack

Longest Common Subsequence

Matrix Chain Multiplication

DP on subsequences

Memoization vs Tabulation


11️⃣ Greedy Algorithms

Activity selection

Huffman coding

Fractional knapsack

Job scheduling


12️⃣ Tries

Insert and search a word

Word search

Auto-complete feature


13️⃣ Bit Manipulation

XOR, AND, OR basics

Check if power of 2

Single Number problem

Count set bits

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MongoDB Learning Roadmap: From Basics to Advanced

1. Getting Started with MongoDB

Introduction to MongoDB: What is MongoDB and why use it? Difference between NoSQL and SQL databases.

Setup: Install MongoDB and Compass (GUI for MongoDB). Set up a local or cloud MongoDB instance using MongoDB Atlas.



2. Core Concepts

Databases and Collections: Understand databases, collections, and documents.

CRUD Operations: Perform Create, Read, Update, and Delete operations using MongoDB shell or Compass.

BSON: Understand how MongoDB stores data in BSON format.



3. Querying Data

Basic Queries: Filter documents using find(). Use operators like $eq, $ne, $lt, $gt, $in, and $nin.

Advanced Queries: Use $and, $or, $not, and $nor. Query arrays and embedded documents.

Projections: Return specific fields using projections in queries.



4. Indexes

Purpose of Indexes: Speed up queries and optimize performance.

Create and Manage Indexes: Single field, compound, and text indexes.

Understand Index Impact: Use the explain() method to analyze query performance.



5. Aggregation Framework

Introduction: Understand the pipeline approach in aggregation.

Basic Stages: $match, $group, $sort, $limit, $project, and $lookup.

Advanced Stages: $unwind, $addFields, $replaceRoot, and $facet.



6. Data Modeling

Schema Design: Differences between embedding and referencing documents.

Relationships: One-to-One, One-to-Many, and Many-to-Many relationships.

Best Practices: Design schemas for scalability and performance.



7. Transactions

Multi-Document Transactions: Implement ACID transactions in MongoDB.

Use Cases: When to use transactions in NoSQL.



8. Working with MongoDB in Applications

MongoDB Drivers: Integrate MongoDB with programming languages like Node.js (Mongoose), Python (PyMongo), and Java.

CRUD Operations in Code: Perform database operations using drivers.



9. Administration and Optimization

Backup and Restore: Use mongodump and mongorestore for backups.

Performance Optimization: Optimize queries, manage indexes, and shard data for horizontal scaling.

Security: Configure authentication, roles, and encryption for secure access.



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