Data Structures Certificate Course

Get Data Structures Certificate Course in Vadodara

Data structures are fundamental concepts in computer science that organize and store data efficiently for easy access and modification. They play a crucial role in optimizing algorithm performance, memory usage, and the scalability of software systems. In software engineering, choosing the right data structure is vital for problem-solving and ensures efficient code execution. Understanding and implementing data structures effectively enhances the development of robust, maintainable software.

Gain hands-on experience with Data Structures Certificate Course through real-world projects and expert mentorship. Earn an industry-recognized certification to boost programming skills in coding and algorithms.

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About Data Structures Certificate Course at KS Technologies

This course is designed to introduce students to fundamental concepts of data structures, which are crucial for efficient algorithm design and implementation. Students will explore the design, implementation, and analysis of various data structures like Arrays, Stacks, Queues, Trees, graphs, Linked Lists, Hashing & many more. Understanding their use in solving computational problems. The course will involve theoretical learning and practical applications, including coding assignments and projects in various programming languages.

Course Curriculum

Introduction to Data Structures Course

This course is designed to introduce students to fundamental concepts of data structures, which are crucial for efficient algorithm design and implementation. Students will explore the design, implementation, and analysis of various data structures, understanding their use in solving computational problems. The course will involve theoretical learning and practical applications, including coding assignments and projects in programming languages like Python, Java, or C++. Course Objectives:

Understand and apply fundamental data structures.
Implement data structures in code.
Analyze the time and space complexity of various operations.
Choose the right data structure based on the problem requirements.
Solve complex computational problems using appropriate data structures.

Course Duration

Total Duration: 12 weeks
Lecture Duration: 3 hours per week
Practical Duration: 2 hours per wee

Prerequisites

Basic knowledge of programming
Understanding of basic algorithms (sorting, searching, etc.)
Familiarity with computational complexity analysis

Course Outline

Week 1: Introduction to Data Structures

Lecture Topics:

What are Data Structures?
Types of Data Structures: Linear vs Non-Linear
Basic Operations (insertion, deletion, searching, etc.)
Abstract Data Types (ADT)
Time and Space Complexity Analysis (Big O, Big Theta, Big Omega)

Practical:

Introduction to Coding Environment
Implementing a Simple Array in Python/Java/C++

Week 2: Arrays and Strings

Lecture Topics:
- Arrays: Definition, Properties, and Operations
- Multi-dimensional Arrays
- Strings: Representation, Operations (concatenation, searching, etc.)
- Applications of Arrays and Strings (e.g., Dynamic Arrays)
Practical:
- Implementing Static and Dynamic Arrays
- String Manipulation Problems (Reverse, Anagram Check)

Week 3: Linked Lists

Lecture Topics:
- Singly Linked Lists: Structure, Operations (Insertion, Deletion, Traversal)
- Doubly Linked Lists: Structure, Operations
- Circular Linked Lists
- Advantages and Disadvantages of Linked Lists
Practical:
- Implementing Singly and Doubly Linked Lists
- Circular Linked List Problems

Week 4: Stacks

Lecture Topics:
- Stack: Definition, Properties, and Operations
- Stack Applications: Expression Evaluation, Balanced Parentheses
- Implementing Stacks Using Arrays and Linked Lists
Practical:
- Implementing a Stack
- Solving Problems like Infix to Postfix Conversion, Parentheses Matching

Week 5: Queues

Lecture Topics:
- Queue: Definition, Operations (Enqueue, Dequeue)
- Circular Queue, Deque (Double-ended Queue)
- Priority Queue: Structure and Operations
- Applications of Queues (e.g., Job Scheduling, BFS)
Practical:
- Implementing Queues using Arrays and Linked Lists

Week 6: Recursion and Backtracking

Lecture Topics:
- Introduction to Recursion: Base Case, Recursive Case
- Stack-based Recursion vs Recursion Trees
- Backtracking: Problem Solving Approach (e.g., N-Queens Problem)
- Tail Recursion and its Optimization
Practical:
- Solving Problems using Recursion (Factorial, Fibonacci)
- Implementing Backtracking Algorithms (e.g., Solving Sudoku)

Week 7: Trees

Lecture Topics:
- Trees: Definition, Terminology, and Types
- Binary Trees, Binary Search Trees (BST)
- Tree Traversals (Inorder, Preorder, Postorder)
- Balanced Trees: AVL, Red-Black Trees
- Heap Data Structure (Min-Heap, Max-Heap)
Practical:
- Implementing Binary Trees and BSTs
- Traversing Trees Using Different Methods
- Heap Construction and Applications

Week 8: Advanced Trees

Lecture Topics:
- B-Trees and B+ Trees
- Splay Trees, Segment Trees
- Trie (Prefix Tree): Structure and Applications
- Tree Rotations and Balancing
Practical:
- Implementing and Traversing B-Trees, Tries
- Applications like Autocomplete using Tries

Week 9: Hashing

Lecture Topics:
- Hash Tables: Concept, Hash Functions, and Collision Resolution
- Open Addressing, Chaining
- Applications of Hashing: Caching, Dictionaries
Practical:
- Implementing Hash Tables with Collision Resolution Techniques
- Solving Problems using Hashing (e.g., Finding duplicate

Week 10: Graphs

Lecture Topics:
- Graphs: Definitions, Representations (Adjacency Matrix, List)
- Types of Graphs: Directed, Undirected, Weighted, Unweighted
- Graph Traversals: BFS, DFS
- Shortest Path Algorithms: Dijkstra’s, Bellman-Ford
Practical:
- Implementing Graphs using Adjacency List and Matrix
- Implementing BFS and DFS Traversals

Week 11: Graph Algorithms

Lecture Topics:
- Minimum Spanning Tree: Kruskal’s and Prim’s Algorithm
- Topological Sorting and its Applications
- Shortest Path Algorithms: Floyd-Warshall Algorithm
- Network Flow Problems
Practical:
- Implementing Kruskal’s and Prim’s Algorithms
- Solving Shortest Path Problems

Note

This syllabus assumes that students are familiar with basic programming concepts. The topics will be adapted based on the programming language chosen, but the core principles of data structures remain consistent across languages.

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Why choose Data Structures Certificate Course at KS Technologies?

Choosing data structures training at KS Technologies ensures a practical, hands-on learning experience tailored to real-world scenarios. With a focus on solving industry-relevant problems, you’ll gain a deep understanding of how data structures enhance software performance. The program includes interactive projects, expert guidance, and a certification that validates your skills, boosting your career prospects in software engineering.

100% Practical based training approach
More than 17 years of industry expertise
Study material with Books & pdfs
Flexible batch timings in weekdays & weekends
Training available in Offline as well Online modes
Free Demo sessions are available

What are the Career opportunities with Data Structures Certificate Course?

A Data Structures Certificate Course opens doors to numerous career opportunities in the tech industry. With a solid foundation in data structures, you can pursue roles such as:

Software Developer/Engineer

Backend Developer

Game Developer

Algorithm Developer

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Data Structures Certificate Course

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About Data Structures Certificate Course at KS Technologies

Course Curriculum

Let's Connect with Us

Why choose Data Structures Certificate Course at KS Technologies?

What are the Career opportunities with Data Structures Certificate Course?

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What our Students say

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