Data Structures and Algorithms (BCS301) Notes — Handwritten Notes
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BCS301

Data Structures and Algorithms notes — handwritten

Complete study material and notes for Data Structures and Algorithms (BCS301) as taught in Semester 3 of B.Tech — Computer Science & Engineering.

The unit order below follows the standard university teaching sequence. Use these topic-wise lecture notes, revision checklists, and important exam questions to structure your exam preparation effectively.

Unit-wise Syllabus & Notes

Unit 1

Arrays, complexity analysis and searching

Notes, worked approach, and a revision checklist.

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Unit 2

Linked lists and their variants

Notes, worked approach, and a revision checklist.

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Unit 3

Stacks, queues and expression evaluation

Notes, worked approach, and a revision checklist.

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Unit 4

Trees, binary search trees, AVL trees and heaps

Notes, worked approach, and a revision checklist.

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Unit 5

Graphs, hashing and sorting techniques

Notes, worked approach, and a revision checklist.

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Frequently Asked Questions

What is the syllabus for Data Structures and Algorithms?

The syllabus is divided into 5 main units: Arrays, complexity analysis and searching, Linked lists and their variants, Stacks, queues and expression evaluation, Trees, binary search trees, AVL trees and heaps, Graphs, hashing and sorting techniques. Each unit covers specific topics essential for university examinations.

Where can I find important questions for Data Structures and Algorithms?

Wink Notes provides unit-wise worked approaches, past-paper analysis, and a revision checklist to help you identify and practice the most important questions for Data Structures and Algorithms.

How many units are in Data Structures and Algorithms?

Data Structures and Algorithms (BCS301) is divided into 5 units: Arrays, complexity analysis and searching, Linked lists and their variants, Stacks, queues and expression evaluation, Trees, binary search trees, AVL trees and heaps, Graphs, hashing and sorting techniques. Each unit is covered with detailed topic-wise lecture notes, worked examples, and a revision checklist.