Data Structures Fundamentals
Discovering key concepts
Code Trail3 of 6
Explore fundamental data structures and algorithms crucial for efficient problem-solving. Learn how to select and implement appropriate data structures to optimize your code performance.
10 Chapters
Concept Explanations & Warm up problems
Learn concepts with detailed explanations and illustrations. Wrap up with practice problems to apply what you've learned.
Challenge Problems
Apply what you've learned to various practice problems and identify any gaps in your understanding.
Test Problems
The final stage of each chapter consists of test problems that you must solve on your own, without solutions or discussion features. With a slightly higher difficulty level, these problems help you refine your skills.
1
Time and Space Complexity
Learn about time and space complexity, and how to calculate them in your code.
Pseudo Code
Asymptotic Notation
Definition of Time Complexity
Time Complexity in For Loop
Time Complexity in Recursion
Space Complexity
2
Linear Data Structures
Explore arrays, linked lists, and other linear data structures.
Array
Vector
Single-LinkedList
Doubly-LinkedList
Iterator
Circular-LinkedList
3
Sorting Algorithms
Learn various sorting algorithms like bubble sort and merge sort, their implementations, and characteristics.
Bubble Sort
Selection Sort
Insertion Sort
Radix Sort
Speed Comparison
Merge Sort
Quick Sort
Heap Sort
Stable Sort
In-Place Sort
4
Binary Search
Understand the concept of binary search and how to use it to reduce time complexity.
Binary Search
Lower Bound & Upper Bound
5
Stack, Queue, and Deque
Learn about stacks, queues, and deques - their definitions, implementations, and applications.
Stack
Queue
Deque
6
Tree Structures
Explore various tree data structures and their applications.
Tree
Binary Tree Concept
Traversal
Binary Search Tree
Heap
7
Hashing Techniques
Learn about string hashing and its applications in problem-solving.
Hashing
8
Dynamic Programming Basics
Understand the concept of dynamic programming and solve various types of problems using this technique.
DP Concept
Memoization
Tabulation
Call themselves that have same shape and merge
One Object Moving in Grid
Optionally Select that meets the conditions
Selecting Items appropriately
String Matching
Greedy Algorithm
9
Graph Basics
Learn different ways to represent graphs and basic graph traversal algorithms.
Graph Concept
Representation
DFS
Traversal
Equal Weighted Graph
10
Advanced Graph Algorithms
Explore crucial graph algorithms, such as those for finding shortest paths and minimum spanning trees in graphs.
Dijkstra
Floyd Warshall
Kruskal
Prim
Topological Sort
Comprehensive understanding of fundamental algorithms and data structures terminology
Ability to recognize which data structure or algorithm is most suitable for specific problem types
Confidence in reading and understanding algorithm discussions and problem solutions
Skill to analyze the efficiency of different algorithms and data structures
Have basic programming knowledge but want to deepen their understanding of algorithms and data structures
Found algorithm studies challenging in the past and want a structured approach to learning
Need to refresh their knowledge of algorithms and data structures
Are preparing for coding tests and need a solid foundation in algorithmic concepts
Want to understand the terminology used in coding challenge discussions and solutions
Have experience in coding but lack knowledge in advanced problem-solving techniques
Feel limited by only using arrays and want to explore more efficient problem-solving methods