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Oppiskele Importance and Applications of Data Structures | Introduction
DSA course
course content

Kurssisisältö

DSA course

book
Importance and Applications of Data Structures

Understanding Complexity

Efficiency is measured in two dimensions: time complexity and space complexity. These define how an algorithm scales with input size.

Big O Notation

Big O notation is a mathematical concept used to describe an algorithm's efficiency. It provides a high-level understanding of how an algorithm behaves as the input size grows.

Big O helps us compare algorithms and choose the most appropriate problem. It’s a lens for evaluating the correctness and scalability of our solutions.

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course content

Kurssisisältö

DSA course

book
Importance and Applications of Data Structures

Understanding Complexity

Efficiency is measured in two dimensions: time complexity and space complexity. These define how an algorithm scales with input size.

Big O Notation

Big O notation is a mathematical concept used to describe an algorithm's efficiency. It provides a high-level understanding of how an algorithm behaves as the input size grows.

Big O helps us compare algorithms and choose the most appropriate problem. It’s a lens for evaluating the correctness and scalability of our solutions.

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Miten voimme parantaa sitä?

Kiitos palautteestasi!

Osio 1. Luku 1
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