This module continues the exploration of recursion, focusing on more complex problems and their recursive solutions. Students will be tasked with implementing and analyzing these solutions.
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This module serves as an introduction to the fundamental concepts of computer science. It familiarizes students with basic programming constructs, problem-solving strategies, and the importance of data structures.
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This module focuses on the first part of C programming. Students will learn about variables, data types, operators, and control structures such as loops and conditionals.
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In this module, students continue to deepen their understanding of C programming with advanced topics. This includes functions, arrays, and pointers.
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This module provides further insights into C programming, focusing on the use of structures and file handling. Students will learn how to create complex data types.
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This module introduces the concept of data structuring through practical case studies. Students will work on real-life examples to understand how to manage data effectively.
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Building upon the previous case study, this module focuses on advanced data structuring techniques. Students will analyze and implement complex data structures.
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This module explores further case studies in data structuring, focusing on the implementation and management of advanced data structures.
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This module introduces the concept of recursion and its applications in problem decomposition. Students will learn the theory behind recursion and practice writing recursive functions.
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This module continues the exploration of recursion, focusing on more complex problems and their recursive solutions. Students will be tasked with implementing and analyzing these solutions.
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In this final recursion module, students will explore advanced concepts and applications of recursion in different algorithms and problem-solving scenarios.
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This module focuses on two fundamental sorting algorithms: mergesort and quicksort. Students will learn the principles behind these algorithms and their implementation in C.
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This module covers characters and strings in C, focusing on their manipulation and usage in programming. Students will learn about string functions and character arrays.
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This module introduces arrays, focusing on how they store data in contiguous memory locations and their practical applications in C programming.
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This module delves into structures in C, exploring how they allow students to create custom data types. Understanding structures is crucial for efficient data management.
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Continuing from the previous module, this session explores advanced topics in structures, including nested structures and pointers to structures, enhancing data organization.
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This module discusses dynamic memory allocation, focusing on how it enables the creation of structures and arrays whose size can change during runtime.
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This module focuses on linked lists, a dynamic data structure that allows efficient insertion and deletion of elements. Students will learn to implement and manipulate linked lists.
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This module covers the complexity and efficiency of algorithms, teaching students to evaluate algorithm performance using Big O notation and other analysis techniques.
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This final module explores asymptotic growth functions, providing students with the tools to analyze how algorithms perform as the size of input data increases.
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This module delves into the Asymptotic Analysis of Algorithms, an essential topic in computer science. Understanding how algorithms perform under different conditions is crucial for optimizing code and ensuring efficiency. Key concepts covered include:
Students will learn to assess the efficiency of algorithms and make informed decisions on algorithm selection based on their performance characteristics.
This module focuses on Data Structuring, which is the foundation of effective programming. It teaches students how to organize data in a way that enables efficient access and modification. Topics include:
By the end of this module, students will be capable of implementing various data structures and understanding their advantages and disadvantages.
This module, Search Trees, introduces students to tree data structures focusing on search operations. Students will learn how trees organize data hierarchically, allowing for efficient searching, inserting, and deleting. Key points include:
By the end of the module, students will understand the importance of search trees in database indexing and data retrieval.
In Search Trees-II, students continue to explore advanced topics related to search trees. This module builds upon the previous module's foundational knowledge, emphasizing performance improvements and complex tree structures. Topics include:
Students will gain insights into optimizing search operations and managing large datasets more effectively.
Search Trees-III extends the knowledge of tree structures, focusing on multi-way trees and their applications. This module introduces students to trees that allow more than two children, facilitating efficient database management and complex data organization. Key topics include:
Students will learn how multi-way trees improve performance in disk-based storage systems.
Lec-25 introduces 2-3 Trees, a specific type of balanced search tree that maintains sorted data and enables efficient searching, insertion, and deletion. This module covers:
Students will understand how 2-3 Trees can be utilized for optimal performance in various scenarios.
Algorithm Design-I lays the groundwork for understanding how to construct algorithms systematically. Students will learn the principles of algorithmic thinking, which include:
This foundational knowledge will prepare students for more complex algorithmic challenges in subsequent modules.
Algorithm Design-II further develops algorithmic techniques introduced in the previous module. This course emphasizes more advanced design strategies, including:
Students will engage in practical exercises that enhance their ability to choose and implement the right algorithm for different problems.
In Algorithm Design-III, students explore specialized algorithms that solve complex problems in various domains. Topics covered include:
This module aims to equip students with the knowledge to apply algorithmic solutions to real-world challenges effectively.
Lec-29 focuses on Graphs-I, where students learn about graph theory fundamentals. They will understand graphs as a powerful tool for modeling relationships in various applications. Topics include:
This foundational knowledge will support students in applying graph theory in real applications such as networking and optimization.
Graphs-II builds on the knowledge acquired in the previous module, exploring advanced graph algorithms and their applications. This module covers:
By mastering these concepts, students will be able to solve complex graph-related problems with confidence.
In Graphs-III, students will explore specialized topics in graph theory, including advanced applications and techniques. This module covers:
Students will gain a deeper understanding of graph properties and learn to apply these concepts in various real-world scenarios.
The final module, Conclusions, synthesizes the knowledge acquired throughout the course. Students will reflect on their learning journey and explore:
This module aims to prepare students for applying their knowledge practically and pursuing further education in computer science.