Data Structures and Algorithms (DSA) Course by Kashish Solanki

The Data Structures and Algorithms (DSA) Course by Kashish Solanki is a structured, beginner-to-intermediate level program designed to build strong problem-solving and algorithmic thinking skills. This course is ideal for students, aspiring software developers, and professionals who want to strengthen their coding foundations and prepare for technical interviews, competitive programming, and real-world software development.

The curriculum follows a step-by-step modular approach that starts with basic concepts and gradually progresses to advanced data structures and algorithm design. Learners will not only understand theoretical concepts but also apply them through practical coding exercises and real problem-solving scenarios. The course emphasizes logical thinking, performance optimization, and clean implementation practices.

With a balanced combination of concept explanation, coding practice, and problem-solving sessions, students develop confidence in writing efficient programs and handling complex data structures.

MODULE 1: Foundations

Week 1: DSA Basics

• What is Data Structure?

• What is Algorithm?

• Importance of DSA

• Abstract Data Types (ADT)

• Types of Data Structures

  • Primitive & Non-Primitive

  • Linear & Non-Linear

Week 2: Time & Space Complexity

• Why complexity analysis?

• Time complexity

• Space complexity

• Asymptotic notations:

  • Big-O

  • Big-Ω

  • Big-Θ

• Best, average & worst cases

• Complexity of simple loops & nested loops

🔹 MODULE 2: Arrays, Strings & Recursion

Week 3: Arrays

• Array basics

• Static vs Dynamic arrays

• Traversal

• Insertion & deletion

• Searching:

  • Linear search

  • Binary search

• Sorting:

  • Bubble sort

  • Selection sort

  • Insertion sort

• Practice problems

Week 4: Strings

• String representation

• String operations

• String comparison

• Palindrome check

• Anagram check

• Practice problems

Week 5: Recursion

• Recursion basics

• Base & recursive case

• Recursion vs iteration

• Stack memory

• Problems:

  • Factorial

  • Fibonacci (simple)

  • Power of a number

🔹 MODULE 3: Linear Data Structures

Week 6: Linked List

• Singly Linked List

• Doubly Linked List

• Circular Linked List

• Operations:

  • Insertion

  • Deletion

  • Traversal

  • Reversal

• Practice problems

Week 7: Stack

• Stack ADT

• Implementation using array & linked list

• Stack operations

• Applications:

  • Balanced parentheses

  • Infix to postfix

  • Postfix evaluation

Week 8: Queue

• Queue ADT

• Linear queue

• Circular queue

• Deque

• Priority queue (basic concept)

• Applications:

  • CPU scheduling (concept)

  • BFS (intro)

🔹 MODULE 4: Non-Linear Data Structures

Week 9: Trees

• Tree terminology

• Binary Tree

• Binary Search Tree (BST)

• Tree traversals:

  • Inorder

  • Preorder

  • Postorder

  • Level order

• Height & depth

• Practice problems

Week 10: Heap

• Heap concept

• Min heap & Max heap

• Heap insertion & deletion

• Heap sort

• Priority queue using heap

Week 11: Hashing

• Hash table

• Hash functions

• Collision handling:

  • Chaining

  • Open addressing

• Applications of hashing

• Practice problems

🔹 MODULE 5: Graphs (Basic Only)

Week 12: Graph Basics

• Graph terminology

• Types of graphs

• Graph representation:

  • Adjacency matrix

  • Adjacency list

• Graph traversal:

  • BFS

  • DFS

• Simple applications

Teaching Method

• Mode: Live interactive online and offline classes

• Step-by-step concept explanation

• Practical coding demonstrations

• Hands-on problem-solving sessions

• Regular practice assignments

• Real-time doubt clearing

• Logical thinking and optimization-focused teaching

• Interview-oriented problem discussion

Why Learn With Kashish Solanki

Kashish Solanki follows a concept-first and practice-driven teaching approach that helps learners understand not just how to implement data structures, but also why they are used. The training emphasizes efficiency, clarity, and structured problem-solving techniques. Students receive guidance that focuses on building strong fundamentals essential for technical interviews and software development roles.

Benefits and Outcomes

• Strong foundation in data structures and algorithms

• Improved logical thinking and coding skills

• Better problem-solving ability

• Confidence in handling technical interview questions

• Preparation for competitive programming basics

• Improved understanding of performance optimization

• Ability to write efficient and structured code