Data Structure Training Course

Data Structure Training

The Data Structure Training at Yuva Sakthi Academy equips participants with a deep understanding of various data structures and their practical applications in programming and algorithm design. This course focuses on enhancing problem-solving skills by teaching how to choose the right data structures to optimize performance in software development.

Upon completing the Data Structure course, participants will receive a recognized certificate of completion, valued by employers in the tech industry. This certification not only strengthens your resume but also improves job prospects in areas like software development, data science, and algorithm engineering. According to industry reports, professionals proficient in data structures can command competitive salaries, reflecting their critical role in technology and software innovation.

Our dedicated career support team assists participants in securing employment by providing personalized coaching in resume building, interview strategies, and effective communication skills. We offer extensive training in technical interviews and algorithm challenges, ensuring that participants are well-prepared for roles in leading tech firms and startups.

About the Data Structure Training Course

The Data Structure Training Course delves into fundamental and advanced topics, including arrays, linked lists, stacks, queues, trees, and graphs. Participants will engage in practical exercises that highlight the use of different data structures in solving complex problems and optimizing code efficiency.

Our curriculum is designed to keep pace with industry standards, ensuring participants acquire the latest techniques and best practices. Through hands-on projects and collaborative assignments, delegates will build the skills necessary for a successful career in software engineering and data analysis.

At Yuva Sakthi Academy, we are committed to supporting our participants' career journeys with 100% placement assistance. Our strong network with companies such as Infosys, Accenture, Wipro, and HCL ensures that you have access to exciting job opportunities in the field of Data Structures and software development. Join us to kickstart your journey towards a fulfilling career in technology!

Module 1: Introduction to Data Structures

Objectives:

• Understand the significance of data structures in computer science across C, C++, Java, and Python.
• Learn about the various types of data structures and how they're implemented in these languages.

Topics:

• What are Data Structures?
• Abstract Data Types (ADT)
• Complexity Analysis: Time and Space Complexity in C, C++, Java, and Python

Module 2: Arrays and Strings

Objectives:

• Master the use of arrays and strings for data storage and manipulation in C, C++, Java, and Python.

Topics:

• Arrays in C, C++, Java, and Python: Definition, Types, and Operations
• String Manipulation and Functions in C, C++, Java, and Python
• Multi-dimensional Arrays in C, C++, and Python

Module 3: Linked Lists

Objectives:

• Learn about the structure and operations of linked lists and how they are implemented in C, C++, Java, and Python.

Topics:

• Introduction to Linked Lists in C, C++, Java, and Python
• Types of Linked Lists: Singly, Doubly, and Circular in each language
• Operations: Insertion, Deletion, Searching in C, C++, Java, and Python

Module 4: Stacks and Queues

Objectives:

• Understand stack and queue data structures and their applications in C, C++, Java, and Python.

Topics:

• Stacks in C, C++, Java, and Python: Definition, Operations, and Applications
• Queues in C, C++, Java, and Python: Types and Operations
• Applications of Stacks and Queues in C, C++, Java, and Python: Expression Evaluation, Backtracking

Module 5: Trees

Objectives:

• Explore tree data structures, their hierarchical properties, and implementation in C, C++, Java, and Python.

Topics:

• Introduction to Trees: Terminology and Properties in C, C++, Java, and Python
• Binary Trees: Traversals, Binary Search Trees (BST) in C, C++, Java, and Python
• Balanced Trees: AVL Trees, Red-Black Trees in C++, Java

Module 6: Graphs

Objectives:

• Understand graph theory and its practical applications in C, C++, Java, and Python.

Topics:

• Graph Representation: Adjacency Matrix, Adjacency List in C, C++, Java, and Python
• Graph Traversal Algorithms: Depth First Search (DFS), Breadth First Search (BFS)
• Shortest Path Algorithms: Dijkstra’s Algorithm, Bellman-Ford Algorithm in each language

Module 7: Hashing

Objectives:

• Learn about hashing techniques for efficient data retrieval in C, C++, Java, and Python.

Topics:

• Introduction to Hashing in C, C++, Java, and Python
• Hash Functions: Characteristics and Types in each language
• Collision Resolution Techniques: Chaining, Open Addressing

Module 8: Advanced Data Structures

Objectives:

• Explore advanced data structures and their specialized applications in C, C++, Java, and Python.

Topics:

• Trie: Definition and Applications in C, C++, Java, and Python
• Segment Trees and Fenwick Trees
• Graphs: Advanced Topics, Minimum Spanning Trees, Network Flow

Module 9: Capstone Project

Objectives:

• Implement a comprehensive project that utilizes various data structures in C, C++, Java, or Python.

Project Guidelines:

• Select a real-world problem suitable for data structure application.
• Design and implement the solution using appropriate data structures in the language of your choice (C, C++, Java, Python).
• Document your process and findings in a comprehensive report.
• Present your project to demonstrate your understanding and application of concepts.