DSA ( Data Structure & Algorithm Course )
Duration 5 To 6 MONTH
Data Structure & Algorithm Course
Data structures and algorithms (DSA) are an important aspect of any programming language. Every language has its own data structures and its way of handling different types of algorithms.
Data Structure Using PYTHON and JAVA training in Gwalior focuses on the significance of data structures and algorithms in computer programming and software development. Hands-on exposure on data structures lays a strong foundation in developing programs. According to the real life scenario, a well versed candidate can distinguish which data structure to be used to drive optimized results.
Data structure and algorithms help in understanding the nature of the problem at a deeper level and thereby a better understanding of the world. Using combination of data structure and algorithms, we can improve performance of program drastically. Are necessary for design of efficient algorithms.allows safe storage of information on a computer.
Table of Contents/Roadma
5 steps to learn DSA from scratch
Learn at least one Programming Language
Learn about Complexities
Learn Data Structure and Algorithms
1) Array
2) String
3) Linked List
4) Searching Algorithm
5) Sorting Algorithm
6) Divide and Conquer Algorithm
7) Stack
8) Queue
9) Tree Data Structure
10) Graph Data Structure
11) Greedy Methodology
12) Recursion
13) Backtracking Algorithm
14) Dynamic Programming
15) HashTables
16) Asymptotic Notations
Practice, practice and practice more
Learn the Fundamentals of chosen Language properly
Focus on Logic Building
Don’t worry if stuck on a problem
Be consistent
Conclusion
Learn at least one
Programming language
This should be your first step while starting to learn data structure and algorithms. We as human beings, before learning to write a sentence or an essay on a topic, first try to learn that language: the alphabet, letters, and punctuations in it, how and when to use them. The same goes for programming also.
Firstly, select a language of your choice, be it Java, C, C++, Python, or any other language of your choice. Before learning how to code in that language you should learn about the building pieces of the language: the basic syntax, the data types, variables, operators, conditional statements, loops, functions, etc. You may also learn the concept of
To help you get started with the language of your choice, we have created a complete course to start as a beginner, such as:
Fork Java Programming – Self Paced
Fork Python Programming – Self Paced
• given a binary digits like 001101 arrange the numbers such that zeroes should follow 1sike 0001111.
• Find Triplets of a+b+c=k in an array
• Next Greater element in an array
• 4.Lead element in an array
• 6.Find unique nos in an array
• 7.Check 2 arrays are equal or not
• 8.K largest elements in an array
• 9.find x and y in an array whose sum is K
• ’10.Merge two sorted arrays without extra space
• 11. Find missing number
• 12. Find missing 2 numbers
Course details-:
- Introduction to Data Structures
Candidate Level
Introduction to Data Structures
Linear Data Structure Applications
Array
Linked List
Stack
Queue
Non-Linear Data Structures
Tree
Graph
Find common prefix
Reverse a String
String Permutations
longest commonsub sequenceLongest increasing sub sequence
Find a word in dictionary
- Introduction
- Construction
- Length
- Insertion
- Deletion
- Sort
- Reverse list
- Swap nodes
- Applications
- Introduction
- Construction
- Length
- Insertion
- Deletion
- Sort
- Reverse list
- Swap nodes
- Applications
- Bubble sort
- Selection sort
- Insertion sort
- Heap sort
- Merge sort
- Quick sort
- Stack Operations
- push()
- pop()
- peek()
- Lenth()
- isEmpty()
- isFull()
- Stack implementation using arrays
- Applications
- Decimal to Binary
- String reverse
- Number reverse
- Recursion – Towers of Hanoi
- Balanced Parentheses
- Expressions
- Operations on Queue – enqueue(), dequeue()
- Queue implementation using static arrays
- Applications
- Queues Implementations using array (dynamic)
- Introduction & Terminology
- Graph Representations
- Traversal
- BFS (Breadth First Search)
- DFS (Depth First Search)
- Kruskals spanning tree
Primes spanning tree
Disjaskra shortest path
Knapsack problem
Min cost path Matrix
Longest common sub sequence
Huffman Coding
- Analysis of factorial problem
- Analysis of fib series
- String permutations
- Towers of Hanoi
Longest common sub sequence
- Min cost path Matrix
- Knapsack problem
- factorial of a numer
- fibanacci series
- pattern matching
- Dynamic Programming Notes
- DP with Arrays Based Problems
- DP with Strings Based Problems
- DP with Maths Based Problems
- DP with Trees Based Problems
- Breaking and Partitioning Based Problems
- Counting Based Problems
- Standard Problem
- Mixed Problem
- Hash Table representation
- Hash function-Division Method
- Collision
- Collision Resolution Techniques
- Separate Chaining
- open addressing
- linear probing
- quadratic probing
- double hashing
- Rehashing
- Hash Table representation
- Hash function-Division Method
- Collision
- Collision Resolution Techniques
- Separate Chaining
- open addressing
- linear probing
- quadratic probing
- double hashing
- Rehashing
- Terminology
- Differences between Tree and Binary Tree
- Binary Tree Representations
- Expression Trees
- Traversals
- In-order
- pre-order
- post-order
Binary Search Tree
Introduction to BST
Insertion
Deletion
Search
Implementation
- Big O
- Omega
- Theta notations
- Introduction to Notations
- Importance of Notations in expression evaluation
- Conversion Algorithms
- Infix to prefix
- Infix to postfix
- Prefix to infix
- Prefix to postfix
- Postfix to infix
- Postfix to prefix
- Implementation of all the conversions
insert
- update
- delete
- search
- setLeft()
- setRight()
- remove()
- removeLeft()
- RemoveRight()
- Bit Manipulation
- Application Based Problems
- Mixed Problems
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