Learn Data Structure & Algorithms the Right Way as Industry needs

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Actual fees INR 45000

ARTH learners NIL

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Program Duration

100+ hours

For every industry in the world the working culture has changed, and hence they need the ones who are specialist for respective programming language. Hence future need arises for understanding individual language wise internal and data structure concepts

First and Only Program which will train you, how to relate current technology real use cases with particular programming language. In other words optimal way of learning DSA

This program is designed keeping in mind that the learners can solve programming challenges, and also face interviews with top-notch companies like Google, Microsoft, Amazon, etc

In other words, the complete program will help you improve your problem- solving skills, and also develop best approach with analytical skills required to understand the real-time use cases of Data Structure & Algorithms rather than memorizing the same.

Note : Does not require any prior knowledge. No Basic knowledge of any programming language ( C++ / Java / Python / Scala / R ) required, we will take you through from basics

Analysis of Algorithm 
Measuring Running time of Algorithms
Worst case, Best case and Average Case Analysis
Abstract Data Types
Big O analysis of Algorithms
Asymptotic Notations
Big O Notation
Omega/Theta Notation
Analysis of common loops
Analysis of Recursion
Space Complexity 
Time Complexity
Euclid’s GCD Algorithm
Applications of Recursion
Operations on Arrays
Binary Search Iterative and Recursive
Stack
Binary Tree in Python
Preorder / inorder / postorder / level order Traversal
Singly Linked Lists
Circular Linked Lists
Doubly Linked Lists
Binary Trees
Binary Search Trees
Binary Search
String Processing
Analysis of Shell Sort
Connectivity in Undirected  / directed Graph
brute-force greedy algorithms 
graph algorithms
dynamic programming
Naive string searching
O(n logn) Sorting
Binary Searching
Greedy Algorithms
Stacks + Queues
Balanced VS Unbalanced BST
Graphs
Sorting Algorithms
Stable VS Unstable Algorithms
Searching + Traversal
Dijkstra + Bellman-Ford Algorithms
Memoization
Big-O Notation
Big-O Values for Array Operations
Bubble/ Insertion/shell / Merge/ Quick / Radix / Stable Counting  Sort
JDK LinkedList Class
Stacks Implementation (Linked List)
Circular Queue Implementation
Queues and the JDK
Hashtables
Linear Probing
Chaining
Storing Heaps as Arrays
Heapsort
Priority Queues
Generalising Recursion
Static and Global Variables in Recursion
Tail / Head / Tree / Indirect / Nested / Factorial Recursion
Tower of Hanoi Problem
Fibonacci Series using Recursion - Memoization
Static vs Dynamic Array
Comparing Strings and Checking Palindrome
Checking if 2 Strings are Anagram (distinct letters)
Diagonal Matrix
C++ class for Diagonal Matrix
Lower Triangular Matrix in C++
Tri-Diagonal and Tri-Band Matrix
Toeplitz Matrix
Sparse Matrix Representation
C++ class for Stack using Linked List
Program for Infix to Postfix Conversion
Queue ADT
Double Ended Queue DEQUEUE
Number of Binary Trees using N Nodes
Internal Nodes vs External Nodes in Binary Tree
Analysis of n-Ary Trees
Generating BST from Preorder
Generating AVL Tree
Red-Black Tree vs 2-3-4 Tree Deletion
Faster Method for creating Heap
Linear / Quadratics Probing
Representation of Undirecteds / directed Graph
Kruskal's Minimum Cost Spanning Tree
Prim's Minimum Cost Spanning Tree
Disjoint Subsets
Asymptotic Notations Big Oh , Omega , Theta
linked lists versus arrays in python
Binary search trees theory - in-order traversal
AVL tree implementation in python
Heap - operations complexities
Dictionaries in Python
Ternary search trees
Adjacency matrix and adjacency list
Memory management: BFS vs DFS
Bellman-Ford algorithms
Spanning trees
Prims-Jarnik
Hybrid algorithms
Functional Queue in Scala
BST in Scala
Scala Tree
Suite of functions exposed on collections such as aggregate, collect, fold, reduce, map, flatMap, scan,partition in Scala
Warshall’s Algorithm in java
Implementation of Depth First Search through Stack
The Imperative Way and a Higher Level of Abstraction
Higher Order Functions
Copy-On-Write, Laziness, and Deferred Execution
Recursion Aids Immutability
Referential Transparency
Persistent Data Structures and Tail Call Optimization
Greedy Algorithms and Backtracking in Scala
0-1 Knapsack problem
Object Oriented Programming
Inner Classes
Binary Search using Recursion in Python
Splay Trees - Zig-Zig Restructuring
Graph Abstract Data Type (ADT)
Graphs - Path and Cycle
Graphs - Degree of a Vertex
Graphs - Subgraphs and Connected Components
Number theory and Mathematical
Modulo Arithmetic Algorithms
Arithmetic and Geometric Progressions
LCM and HCF
Bitwise Operators in C++ / Java / Python / Scala
Stability in Sorting Algorithms
Rabin Karp Algorithm
Backtracking
R Data Frame
Generalized Linear Models in R
ANOVA model in R
Chi-Square Test in R
Survival Analysis in R Programming
Solving Anagrams
Runtime Complexity