Object-Oriented Data Structures in C++

• Understand the fundamentals of object-oriented data structures and their real-world applications.
• Describe the properties and operations of Binary Search Trees, AVL trees, and other search trees.
• Implement various tree-based data structures and perform operations like insert, delete, and search.
• Analyze heap structures for priority queue implementation and dynamic memory management.
• Develop algorithms for constructing and balancing AVL and Red-Black Trees.
• Apply disjoint set operations in the context of union-find and fast find problems.
• Compare graph traversal methods such as DFS and BFS for efficient searching.
• Construct Minimum Spanning Trees using Prim’s and Kruskal’s algorithms.
• Differentiate among sorting techniques and their time complexities.
• Demonstrate programming ability through the practical implementation of all studied data structures.

• Explain how different object-oriented data structures optimize data handling and processing.
• Identify suitable tree structures like BST, AVL, and Red-Black trees for specific use cases.
• Write C++ programs to perform insertion, deletion, and searching on various trees.
• Evaluate heap operations for effective use in real-time priority queue problems.
• Balance AVL trees using rotations and apply Red-Black Tree transformations.
• Utilize union-find algorithms in problems involving disjoint subsets.
• Perform depth-first and breadth-first graph traversals to explore complex data networks.
• Build Minimum Spanning Trees using standard algorithms like Prim’s and Kruskal’s.
• Assess the efficiency of various sorting methods based on input data and use-case.
• Create functional C++ programs integrating multiple data structures for given problem statements.

The Academic Approach of the course focuses on the “work centric” education i.e. begin with work (and not from a book !), derive knowledge from work and apply that knowledge to make the work more wholesome, useful and delightful. The ultimate objective is to empower the Learner to engage in socially useful and productive work. It aims at leading the learner to his/her rewarding career as well as development of the society.

Learning methodology

• Learners are given an overview of the course and its connection to life and work.
• Learners are then exposed to the specific tool(s) used in the course through the various real-life applications of the tool(s).
• Learners are then acquainted with the careers and the hierarchy of roles they can perform at workplaces after attaining increasing levels of mastery over the tool(s).
• Learners are then acquainted with the architecture of the tool or Tool Map so as to appreciate various parts of the tool, their functions and their inter-relations.
• Learners are then exposed to simple application development methodology by using the tool at the beginner’s level
• Learners then perform the differential skills related to the use of the tool to improve the given ready-made outputs.
• Learners are then engaged in appreciation of real-life case studies developed by the experts.
• Learners are then encouraged to proceed from appreciation to imitation of the experts.
• After imitation experience, they are required to improve the expert’s outputs so that they proceed from mere imitation to emulation.
• Finally, they develop the integral skills involving optimal methods and best practices to produce useful outputs right from scratch, publish them in their ePortfolio and thereby proceed from emulation to self-expression.

Evaluation Pattern of KLiC Courses consists of 4 Sections as per below table:

MKCL’s KLiC Certificate will be provided to the learner who will satisfy the below criteria:

1. Learners who have successfully completed above mentioned 3 Sections i.e. Section 1, Section 2 and Section 3
2. Additionally, learner should have completed Section 4 (i.e. Section 4 will comprise of SUPWs i.e. Socially Useful and Productive Work in form of Assignments)
   • Learner has to complete and upload minimum 2 out of 5 Assignments