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Data Structures and Algorithms (DSA) Fundamentals

Master the essential building blocks of computer science and software engineering. Learn time and space complexity, asymptotic analysis, arrays, linked lists, and algorithm optimization in C/C++, Java, and Python.

0 Students
7 Lessons
35 min Duration
Updated 08/2026 English Lifetime Access

Explore related topics

DSA Data Structures Algorithms Big-O Asymptotic Analysis Arrays Linked Lists C Programming Computer Science

Requirements

  • • Basic familiarity with any programming language (C, C++, Java, or Python)
  • • A computer running Windows, Linux, or macOS
  • • A text editor or IDE (VS Code, Code::Blocks, or CLI tools)

Description

No matter which programming language you use, if you want to build high-performance and scalable systems, mastering Data Structures and Algorithms (DSA) is fundamental.

Data structures provide the organized blueprints for managing and storing information efficiently, while algorithms deliver the step-by-step logic required to process and search data at scale.

What You Will Learn:

  • Core definitions, interfaces, and implementations of modern data structures.
  • Setting up local compilers and IDEs for C, C++, Java, and Python.
  • Characteristics of effective algorithms: correctness, feasibility, and finiteness.
  • Asymptotic analysis: mastering Big-O ($O$), Big-Omega ($\Omega$), and Big-Theta ($\Theta$) notations.
  • Best-case, Average-case, and Worst-case runtime scenarios.
  • Contiguous memory storage, element addressing, and multi-dimensional array operations.
  • Dynamic memory allocation and pointer-based Singly, Doubly, and Circular Linked Lists.

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