Udemy – Time and space complexity analysis (big-O notation)

৳ 99.00

Master Time & Space Complexity Analysis Using Big O Notation

✅ আপনি যদি অর্ডার সম্পন্ন করার 1 ঘণ্টার মধ্যে আপনার ইমেইল ইনবক্স বা স্প্যাম ফোল্ডারে কোর্স ডাউনলোড লিংক না পান, তাহলে দয়া করে আমাদের হোয়াটসঅ্যাপ সাপোর্ট টিমের সাথে যোগাযোগ করুন: 01987186749। আমরা আপনার সহায়তায় সর্বদা প্রস্তুত।

Description

Course Requirements

  • Basic programming knowledge


Course Description

Master Time and Space Complexity Analysis with this comprehensive, step-by-step course designed for programmers, computer science students, and competitive coders. If you struggle with Big-O notation, algorithm efficiency, or complexity classes, this course will give you a strong foundation to analyze and optimize algorithms with confidence.

This course blends theory + practical examples, helping you understand how to evaluate algorithm performance in real-world coding scenarios. You’ll explore essential concepts like Big-O, Big-Theta, amortized analysis, recursion complexity, and the efficiency of common data structures and algorithms.

With well-structured lessons, engaging animations, clear explanations, quizzes, and downloadable resources, this course ensures a smooth and enjoyable learning experience.


What You Will Learn

This course covers everything you need to understand algorithm complexity thoroughly:

Fundamentals of Algorithm Analysis

  • Basics of time and space complexity

  • Why complexity analysis matters in coding, interviews, and system design

Complexity Notations Explained

  • Big-O, Big-Ω (Omega), and Big-Θ (Theta)

  • Best, average, and worst-case scenarios

Deep Dive Into Complexity Concepts

  • Complexity hierarchy

  • Complexity classes, including P vs NP

  • Amortized time complexity explained

Practical Complexity Analysis

  • How to analyze the time and space complexity of any algorithm

  • Comparing algorithm efficiency

  • Understanding recursion complexity

Real-World Use Cases

  • Complexity analysis of:

    • Searching algorithms

    • Sorting algorithms

    • Common data structure operations

    • Popular coding interview problems

Avoid Common Mistakes

  • Misconceptions and errors developers often make while analyzing complexity


Who Should Enroll?

This course is ideal for:

  • Programmers and software developers

  • Computer Science and Engineering students

  • Competitive programmers

  • Self-taught coders aiming to improve problem-solving skills

Please Note: Files will be included in this purchase only Full Course Video & Course Resources. You will get cloud storage download link with life time download access.

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