Data Structures and Algorithms Basics

Learn the fundamentals of data structures and algorithms, including Big O notation, arrays, and linked lists, with Java implementation examples.

Coursified Library ↗

source: Programming with Mosh

Outline · 14 modules · quiz after each

01IntroductionData structures and algorithms are a common topic in coding interviews1 min

02PrerequisitesBasic programming knowledge is required to follow along1 min

03Big O Notation and Constant TimeBig O notation describes the performance and scalability of an algorithm4 min

04Linear Time ComplexityLinear time complexity O(n) grows in direct proportion to the input size2 min

05Linear Time with Multiple InputsIterating over two separate inputs results in O(n + m) complexity1 min

06Quadratic, Cubic, Logarithmic, and Exponential TimeNested loops create quadratic O(n^2) or cubic O(n^3) complexity6 min

07Space ComplexitySpace complexity measures the amount of memory an algorithm requires relative to input size2 min

08Course PromotionoptionalThe speaker offers a full 13-hour course on data structures and algorithms1 min

09Arrays: Theory and Java SyntaxArrays store items sequentially in memory, enabling O(1) access by index7 min

10Building a Dynamic Array: Insert and ResizeA custom array class can track item count and insert elements at the end11 min

11Building a Dynamic Array: Remove and SearchRemoving an element requires shifting subsequent elements to the left to fill the gap7 min

12Java Built-in Dynamic ArraysJava provides ArrayList and Vector classes for dynamic arrays4 min

13Linked Lists: Structure and DeletionLinked lists consist of nodes that hold data and a reference to the next node5 min

14Java Linked Lists SyntaxThe Java LinkedList class supports adding and removing items from both ends2 min

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Details

Duration1h 19m

Assessment13 questions · pass 70%

Quiz questions123

LanguageEnglish

CertificateYes · verifiable

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