Module 1 - Getting Started with C++ Programming
Learn the fundamentals of programming and dive into C++ concepts, including execution process and programming paradigms.
Module 2 - Fundamentals of C++
Learn the foundational concepts of C++ programming, including variables, data types, and their scope within programs.
Module 3 - Control Flow & Loops
Understand the core concepts of control flow in C++, including conditional statements, loops, and jump statements to structure logical execution in programs.
Module 4 - Functions & Pointers
Learn the fundamentals of functions and pointers in C++, including their importance, types, memory management, and common interview questions.
Module 5 - Object-Oriented Programming in C++ and Java
This module provides a structured approach to mastering Object-Oriented Programming (OOP) in Java. It covers fundamental concepts such as classes & objects and access modifiers, focusing on encapsulation, reusability, and best practices for developing robust Java applications.
Module 6 - Standard Template Library (STL)
Explore the fundamentals of STL in C++, including sequential and associative containers, their advantages, and implementation in programming.
Module 7 - Data Structures & Algorithms
Learn the fundamentals of data structures and algorithms, their significance in problem-solving, efficiency considerations, and performance analysis techniques.
Module 8 - Arrays & Strings in C++
Understand the fundamental concepts of arrays and strings in C++, including memory allocation, common operations, and their functions in programming.
Module 9 - Recursion and Its Use Cases
Learn the fundamental concepts of recursion in programming, its types, applications, best practices, and how it is used in algorithms and problem-solving.
Module 10 - Searching and Sorting
Learn the fundamental concepts of searching and sorting algorithms, their efficiency, implementation strategies, and real-world applications.
Module 11 - Array & String Patterns
Learn various array and string problem-solving techniques including Two Pointers, Sliding Window, and Prefix Sum, along with practical applications.
Module 12 - Array & String Algorithms
Learn key algorithms for arrays and strings, including searching, partitioning, pattern matching, and optimization techniques used in competitive programming and real-world applications.
Module 13 - Backtracking and Its Applications
Learn the principles of backtracking, recursive exploration techniques, optimization strategies, and applications in graph traversal and combinatorial problems.
Module 14 - Hashing and Its Applications
Learn the fundamentals of hashing, its role in data structures and algorithms, collision resolution techniques, and practical applications in competitive programming and real-world scenarios.
Module 15 - Linked Lists for DSA
Learn about linked lists, their types, operations, advantages, and practical implementations in data structures and algorithms.
Module 16 - Linked List Patterns
Explore different techniques for solving linked list problems, including slow & fast pointers and in-place reversal methods. Learn efficient problem-solving strategies used in data structures and algorithms.
Module 17 - Stack, Queue, and Deque
Learn the fundamental concepts of stack, queue, and deque, their operations, applications in problem-solving, and advanced techniques like monotonic structures.
Module 18 - Tree Data Structures
Learn about tree-based data structures, including binary trees, binary search trees, and N-ary trees, along with traversal techniques and problem-solving strategies.
Module 19 - Tree Patterns
Explore advanced tree traversal techniques, different tree views, and various methods for constructing trees used in data structures and algorithms.
Module 20 - Heap and Priority Queue
Learn about heap data structures and priority queues, their operations, variants, applications in real-world scenarios, and practice problems.
Module 21 - Heap & Priority Queue Patterns
Explore key problem-solving patterns using heaps and priority queues, including Kth element selection, K-way merging, and dynamic median tracking.
Module 22 - Trie (Prefix Tree)
Explore the Trie data structure, its operations, variants, algorithms, and applications in text processing, network routing, and efficient searching.
Module 23 - Interval & Design-Based Problems
Learn various techniques for solving interval-based problems efficiently and explore key design patterns for real-world applications.
Module 24 - Graph Data Structure
Explore the fundamental concepts of graph theory, including representations, traversal techniques, shortest path algorithms, and applications in real-world scenarios.
Module 25 - Dynamic Programming
Master dynamic programming concepts, including problem-solving approaches, optimization techniques, and real-world applications to improve algorithmic efficiency.
Module 26 - Greedy Algorithm for Problem Solving
Learn the principles of greedy algorithms, their approaches, and applications in optimization problems, scheduling, graph traversal, and resource allocation.
Module 27 - Bit Manipulation
Explore the power of bitwise operations in programming, optimization techniques, dynamic programming, and graph algorithms using bit manipulation strategies.
Module 28 - Segment Tree
Learn the fundamentals of segment trees, their applications in range queries, lazy propagation, advanced techniques, and their use in graph algorithms and string processing.
Module 29 - Combinatorics
Learn the principles of combinatorics, including counting techniques, permutations, combinations, and their applications in probability, graph theory, and dynamic programming.
Module 30 - String Matching
Learn string matching algorithms, including exact and approximate matching techniques, their applications in search engines, DNA sequencing, plagiarism detection, and advanced computational strategies.