Analysis of Algorithms

  • 4.5
Approx. 21 hours to complete

Course Summary

This course covers the fundamentals of analyzing algorithms and their efficiency. You'll learn how to analyze the performance of algorithms and use that knowledge to develop more efficient solutions to problems.

Key Learning Points

  • Understand the basics of algorithm analysis and the big O notation
  • Learn to analyze the efficiency of different algorithms and choose the best one for a given problem
  • Develop algorithms to solve problems in a more efficient way

Job Positions & Salaries of people who have taken this course might have

  • Software Developer
    • USA: $85,000
    • India: ₹6,00,000
    • Spain: €30,000
  • Data Scientist
    • USA: $120,000
    • India: ₹10,00,000
    • Spain: €45,000
  • Computer Systems Analyst
    • USA: $85,000
    • India: ₹6,00,000
    • Spain: €30,000

Related Topics for further study


Learning Outcomes

  • Develop a deep understanding of algorithm analysis and efficiency
  • Be able to choose the best algorithm for a given problem
  • Develop new algorithms to solve problems more efficiently

Prerequisites or good to have knowledge before taking this course

  • Basic knowledge of programming
  • Familiarity with data structures

Course Difficulty Level

Intermediate

Course Format

  • Online
  • Self-paced
  • Video lectures

Similar Courses

  • Algorithms, Part I
  • Algorithms, Part II
  • Introduction to Data Science in Python

Related Education Paths


Related Books

Description

This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. In addition, this course covers generating functions and real asymptotics and then introduces the symbolic method in the context of applications in the analysis of algorithms and basic structures such as permutations, trees, strings, words, and mappings.

All the features of this course are available for free. It does not offer a certificate upon completion.

Outline

  • Analysis of Algorithms
  • History and Motivation
  • A Scientific Approach
  • Example: Quicksort
  • Resources
  • Getting Started
  • Exercises from Lecture 1
  • Analysis of Algorithms
  • Recurrences
  • Computing Values
  • Telescoping
  • Types of Recurrences
  • Mergesort
  • Master Theorem
  • Exercises from Lecture 2
  • Pop Quiz on Telescoping
  • Pop Quiz on the Master Theorem
  • Recurrences
  • Generating Functions
  • Ordinary Generating Functions
  • Counting with Generating Functions
  • Catalan Numbers
  • Solving Recurrences
  • Exponential Generating Functions
  • Exercises from Lecture 3
  • Generating Functions
  • Asymptotics
  • Standard Scale
  • Manipulating Expansions
  • Asymptotics of Finite Sums
  • Bivariate Asymptotics
  • Exercises from Lecture 4
  • Asymptotics
  • Analytic Combinatorics
  • The Symbolic Method
  • Labelled Objects
  • Coefficient Asymptotics
  • Perspective
  • Errata
  • Exercises from Lecture 5
  • Analytic Combinatorics
  • Trees
  • Trees and Forests
  • Binary Search Trees
  • Path Length
  • Other Types of Trees
  • Exercises from Lecture 6
  • Trees
  • Permutations
  • Basics
  • Sets of Cycles
  • Left-Right-Minima
  • Other Parameters
  • BGFs and Distributions
  • Exercises from Lecture 7
  • Permutations
  • Strings and Tries
  • Bitstrings with Restrictions
  • Languages
  • Tries
  • Trie Parameters
  • Exercises
  • Exercises from Lecture 8
  • Strings and Tries
  • Words and Mappings
  • Words
  • Birthday Problem
  • Coupon Collector Problem
  • Hash Tables
  • Mappings
  • Exercises
  • Exercises from Lecture 9
  • Strings and Words

Summary of User Reviews

The Analysis of Algorithms course on Coursera has received high ratings from users. Many users have praised the detailed explanations provided by the instructor.

Key Aspect Users Liked About This Course

Detailed explanations provided by the instructor

Pros from User Reviews

  • Well-structured course material
  • Challenging assignments that helped to deepen understanding
  • Engaging and knowledgeable instructor
  • Good mix of theoretical and practical concepts
  • Great community support

Cons from User Reviews

  • Some assignments were too difficult for beginners
  • Limited interaction with the instructor
  • Some sections were too fast-paced
  • Lack of practical examples in some topics
  • Some users found the course too theoretical
English
Available now
Approx. 21 hours to complete
Robert Sedgewick
Princeton University
Coursera

Instructor

Robert Sedgewick

  • 4.5 Raiting
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