Why Do We Need Data Structures?
In this course, we will focus mainly on data structures. However, algorithms and data structures go hand in hand with each other. Algorithms use data structures to manipulate the data effectively.
We can define a data structure as one that can store some logically connected data so that this data can be processed efficiently. And it is very important to have a way to process large amounts of data efficiently because if we have a lot of data, it often takes a lot of time to process it if the data is unstructured.
Suppose you are developing a GPS navigation application, and the task is to find the shortest route between two locations on a map with multiple interconnected roads.
In this case, you can use a graph data structure, specifically a weighted graph, to optimize the task of finding the shortest route. The map can be represented as a graph, where intersections are nodes, and roads are edges with associated distances (weights). Algorithms like Dijkstra's algorithm or A* search can then efficiently find the shortest path between two locations by traversing this graph.
But how can we assess the quality improvement of our algorithm with the usage of the right data structure? That's what we will talk about in the next chapters.
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Зміст курсу
Algorithms and Data Structures Overview
Algorithms and Data Structures Overview
Why Do We Need Data Structures?
In this course, we will focus mainly on data structures. However, algorithms and data structures go hand in hand with each other. Algorithms use data structures to manipulate the data effectively.
We can define a data structure as one that can store some logically connected data so that this data can be processed efficiently. And it is very important to have a way to process large amounts of data efficiently because if we have a lot of data, it often takes a lot of time to process it if the data is unstructured.
Suppose you are developing a GPS navigation application, and the task is to find the shortest route between two locations on a map with multiple interconnected roads.
In this case, you can use a graph data structure, specifically a weighted graph, to optimize the task of finding the shortest route. The map can be represented as a graph, where intersections are nodes, and roads are edges with associated distances (weights). Algorithms like Dijkstra's algorithm or A* search can then efficiently find the shortest path between two locations by traversing this graph.
But how can we assess the quality improvement of our algorithm with the usage of the right data structure? That's what we will talk about in the next chapters.
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