Data Structures Algorithms Practice Exam

Data Structures Algorithms

 

About Data Structures Algorithms

A specified place that may be used to store and arrange data is called a data structure. Additionally, an algorithm is a series of procedures used to solve a certain issue. We may create computer programs that are effective and optimized by learning data structures and algorithms.

Data structures algorithms has gained immense popularity across the globe resulting in huge demand for certified professionals.

Skills Required 

• Foundational Programming Skills
• Problem-Solving & Logical Thinking
• Understanding of Data Structures
• Understanding of Algorithms
• Time and Space Complexity Analysis
   

Why is Data Structures Algorithms important?

Algorithms and data structures rank among the most crucial components in computer science. We can organize and store data using data structures, and process it meaningfully using algorithms.

Programmers' coding abilities and their familiarity with data structures and algorithms are defined. As a result, understanding and using the data structure for a software developer becomes inescapably important.

Data structures algorithms certified professionals, executives and managers are in high demand in companies across the globe.

 

Who should take the Data Structures Algorithms Exam?

• Programmers
• Software Engineer
• Interview Engineer
• Cloud Software Engineer
• Software Developer
• Staff Engineer
• Beginners in learning Computer Science Subjects

 

Knowledge and Skills required for the Data Structures Algorithms

Candidates gain quick success in career of data structures algorithms if they have skills of critical thinking and good communication skills.

 

Data Structures Algorithms Practice Exam Objectives

Data Structures Algorithms exam focuses on assessing your skills and knowledge in programming, data structures and their algorithms.

 

Data Structures Algorithms Practice Exam Pre-requisite

There are no prerequisites for the Data Structures Algorithms exam. Candidates who are well versed  in programming, data structures and their algorithms can easily clear the exam.

Data Structures Algorithms Certification Course Outline

Module 1: Introduction to Algorithms

• What is an Algorithm?
• Characteristics of Algorithms
• Asymptotic Analysis: Big O, Omega, Theta
• Time & Space Complexity Examples

Module 2: Basic Data Structures

• Arrays and Strings
• Array operations (Insert, Delete, Traverse)
• String manipulation techniques
• Sliding Window Technique
• Two Pointer Approach
• Linked Lists
• Singly, Doubly, and Circular Linked Lists
• Operations: Insert, Delete, Reverse
• Detecting and removing loops
• Merge two sorted linked lists
• Stacks and Queues
• Stack implementation using arrays and linked lists
• Infix, Postfix, Prefix conversions
• Queue types: Simple, Circular, Deque, Priority Queue
• Applications of Stack and Queue

Module 3: Trees

• Binary Trees and Binary Search Trees (BST)
• Tree Traversals: Inorder, Preorder, Postorder, Level Order
• Height, Diameter, Balance of a Tree
• Lowest Common Ancestor (LCA)
• AVL Trees, Segment Trees, and Trie (Basic introduction)

Module 4: Hashing

• Hash Tables and Hash Functions
• Collision Handling Techniques
• Applications of Hashing: Anagrams, Subarray with 0 sum, etc.
• Count Frequency, Hash Maps in practice

Module 5: Sorting and Searching

• Sorting Algorithms: Bubble, Selection, Insertion
• Efficient Sorts: Merge Sort, Quick Sort, Heap Sort
• Binary Search and its Variants
• Order Statistics, Search in Rotated Array

Module 6: Recursion and Backtracking

• Recursion basics, Tail Recursion
• N-Queens Problem
• Rat in a Maze
• Subsets, Permutations, Combinations
• Sudoku Solver

Module 7: Dynamic Programming (DP)

• Memoization vs Tabulation
• Classical DP Problems:
• Fibonacci, Coin Change
• Longest Common Subsequence (LCS)
• 0/1 Knapsack Problem
• Matrix Chain Multiplication
• Longest Increasing Subsequence (LIS)

Module 8: Greedy Algorithms

• Activity Selection
• Huffman Encoding
• Fractional Knapsack
• Job Scheduling

Module 9: Graph Algorithms

• Graph Representations: Adjacency Matrix/List
• Traversals: BFS and DFS
• Shortest Path: Dijkstra, Bellman-Ford
• MST: Kruskal’s and Prim’s Algorithm
• Topological Sort
• Cycle Detection (Undirected and Directed Graphs)

Module 10: Advanced Topics (Optional for Interviews)

• Disjoint Set Union (DSU)
• Trie (Prefix Tree)
• Segment Trees & Binary Indexed Trees
• Fenwick Tree
• KMP Algorithm for Pattern Matching

 

Exam Format and Information

Certification name – Certificate in Data Structures Algorithms
Exam duration – 60 minutes
Exam type - Multiple Choice Questions
Eligibility / pre-requisite - None
Exam language - English
Exam format - Online
Passing score - 25
Exam Fees  - INR 1199