#
Best of Coursera

Top **Algorithms** Courses

These are the **top 32 Algorithms**
courses and offerings found from analyzing all discussions on
Reddit that mention any
Coursera course.

#1

Algorithms, Part I

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations.

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations.

Princeton University

Kevin Wayne

Kevin Wayne

1 reddit posts

385 mentions

385 mentions

#2

Algorithms
Specialization

Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth.

Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth.

Stanford University

Tim Roughgarden

Tim Roughgarden

1 reddit posts

189 mentions

189 mentions

#3

Fundamentals of Computing
Specialization

This Specialization covers much of the material that first-year Computer Science students take at Rice University.

This Specialization covers much of the material that first-year Computer Science students take at Rice University.

Rice University

John Greiner

John Greiner

1 reddit posts

263 mentions

263 mentions

#4

Data Structures and Algorithms
Specialization

This specialization is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems and will implement about 100 algorithmic coding problems in a programming language of your choice.

This specialization is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems and will implement about 100 algorithmic coding problems in a programming language of your choice.

University of California San Diego

Alexander S. Kulikov

Alexander S. Kulikov

3 reddit posts

219 mentions

219 mentions

#5

Algorithms, Part II

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations.

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations.

Princeton University

Robert Sedgewick

Robert Sedgewick

0 reddit posts

151 mentions

151 mentions

#6

Object Oriented Programming in Java
Specialization

This Specialization is for aspiring software developers with some programming experience in at least one other programming language (e.

This Specialization is for aspiring software developers with some programming experience in at least one other programming language (e.

Duke University

Owen Astrachan

Owen Astrachan

0 reddit posts

111 mentions

111 mentions

#7

Bioinformatics
Specialization

Join Us in a Top 50 MOOC of All Time! How do we sequence and compare genomes? How do we identify the genetic basis for disease? How do we construct an evolutionary Tree of Life for all species on Earth? When you complete this Specialization, you will learn how to answer many questions in modern bi...

Join Us in a Top 50 MOOC of All Time! How do we sequence and compare genomes? How do we identify the genetic basis for disease? How do we construct an evolutionary Tree of Life for all species on Earth? When you complete this Specialization, you will learn how to answer many questions in modern bi...

University of California San Diego

Pavel Pevzner

Pavel Pevzner

1 reddit posts

92 mentions

92 mentions

#8

Java Programming and Software Engineering Fundamentals
Specialization

Take your first step towards a career in software development with this introduction to Java—one of the most in-demand programming languages and the foundation of the Android operating system.

Take your first step towards a career in software development with this introduction to Java—one of the most in-demand programming languages and the foundation of the Android operating system.

Duke University

Susan H. Rodger

Susan H. Rodger

1 reddit posts

125 mentions

125 mentions

#9

Probabilistic Graphical Models
Specialization

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other.

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other.

Stanford University

Daphne Koller

Daphne Koller

3 reddit posts

40 mentions

40 mentions

#10

Computer Science

Programming with a Purpose

The basis for education in the last millennium was “reading, writing, and arithmetic;” now it is reading, writing, and computing.

Programming with a Purpose

The basis for education in the last millennium was “reading, writing, and arithmetic;” now it is reading, writing, and computing.

Princeton University

Robert Sedgewick

Robert Sedgewick

0 reddit posts

19 mentions

19 mentions

#11

Algorithmic Toolbox

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming.

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming.

University of California San Diego

Alexander S. Kulikov

Alexander S. Kulikov

0 reddit posts

33 mentions

33 mentions

#12

Accelerated Computer Science Fundamentals
Specialization

Topics covered by this Specialization include basic object-oriented programming, the analysis of asymptotic algorithmic run times, and the implementation of basic data structures including arrays, hash tables, linked lists, trees, heaps and graphs, as well as algorithms for traversals, rebalancing a...

Topics covered by this Specialization include basic object-oriented programming, the analysis of asymptotic algorithmic run times, and the implementation of basic data structures including arrays, hash tables, linked lists, trees, heaps and graphs, as well as algorithms for traversals, rebalancing a...

University of Illinois at Urbana-Champaign

Wade Fagen-Ulmschneider

Wade Fagen-Ulmschneider

0 reddit posts

20 mentions

20 mentions

#13

Introduction to Programming in C
Specialization

This specialization develops strong programming fundamentals for learners who want to solve complex problems by writing computer programs.

This specialization develops strong programming fundamentals for learners who want to solve complex problems by writing computer programs.

Duke University

Andrew D. Hilton

Andrew D. Hilton

2 reddit posts

27 mentions

27 mentions

#14

Mastering the Software Engineering Interview

You’ve hit a major milestone as a computer scientist and are becoming a capable programmer.

You’ve hit a major milestone as a computer scientist and are becoming a capable programmer.

University of California San Diego

Mia Minnes

Mia Minnes

0 reddit posts

18 mentions

18 mentions

#15

Algorithmic Thinking (Part 1)

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language.

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language.

Rice University

Luay Nakhleh

Luay Nakhleh

0 reddit posts

19 mentions

19 mentions

#16

Divide and Conquer, Sorting and Searching, and Randomized Algorithms

The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).

The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).

Stanford University

Tim Roughgarden

Tim Roughgarden

1 reddit posts

12 mentions

12 mentions

#17

Finding Hidden Messages in DNA (Bioinformatics I)

Named a top 50 MOOC of all time by Class Central! This course begins a series of classes illustrating the power of computing in modern biology.

Named a top 50 MOOC of all time by Class Central! This course begins a series of classes illustrating the power of computing in modern biology.

University of California San Diego

Pavel Pevzner

Pavel Pevzner

0 reddit posts

11 mentions

11 mentions

#18

Code Yourself! An Introduction to Programming

Have you ever wished you knew how to program, but had no idea where to start from? This course will teach you how to program in Scratch, an easy to use visual programming language.

Have you ever wished you knew how to program, but had no idea where to start from? This course will teach you how to program in Scratch, an easy to use visual programming language.

The University of Edinburgh

Dr Areti Manataki

Dr Areti Manataki

0 reddit posts

18 mentions

18 mentions

#19

Java Programming

Solving Problems with Software

Learn to code in Java and improve your programming and problem-solving skills.

Solving Problems with Software

Learn to code in Java and improve your programming and problem-solving skills.

Duke University

Owen Astrachan

Owen Astrachan

0 reddit posts

25 mentions

25 mentions

#20

Algorithms for DNA Sequencing

We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data.

We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data.

Johns Hopkins University

Ben Langmead, PhD

Ben Langmead, PhD

0 reddit posts

10 mentions

10 mentions

#21

Interactive Computer Graphics

Computer graphics can be a powerful tool for supporting visual problem solving, and interactivity plays a central role in harnessing the users' creativity.

Computer graphics can be a powerful tool for supporting visual problem solving, and interactivity plays a central role in harnessing the users' creativity.

The University of Tokyo

Takeo Igarashi

Takeo Igarashi

0 reddit posts

15 mentions

15 mentions

#22

Principles of Computing (Part 1)

This two-part course builds upon the programming skills that you learned in our Introduction to Interactive Programming in Python course.

This two-part course builds upon the programming skills that you learned in our Introduction to Interactive Programming in Python course.

Rice University

Scott Rixner

Scott Rixner

0 reddit posts

17 mentions

17 mentions

#23

Genome Sequencing (Bioinformatics II)

You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome? Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end.

You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome? Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end.

University of California San Diego

Pavel Pevzner

Pavel Pevzner

0 reddit posts

5 mentions

5 mentions

#24

Principles of Computing (Part 2)

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science.

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science.

Rice University

Scott Rixner

Scott Rixner

0 reddit posts

7 mentions

7 mentions

#25

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).

The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).

Stanford University

Tim Roughgarden

Tim Roughgarden

0 reddit posts

6 mentions

6 mentions

#26

Algorithmic Thinking (Part 2)

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language.

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language.

Rice University

Luay Nakhleh

Luay Nakhleh

0 reddit posts

6 mentions

6 mentions

#27

Graph Search, Shortest Paths, and Data Structures

The primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social n...

The primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social n...

Stanford University

Tim Roughgarden

Tim Roughgarden

0 reddit posts

4 mentions

4 mentions

#28

Probabilistic Graphical Models 3

Learning

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other.

Learning

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other.

Stanford University

Daphne Koller

Daphne Koller

0 reddit posts

1 mentions

1 mentions

#29

Programming Fundamentals

Programming is an increasingly important skill, whether you aspire to a career in software development, or in other fields.

Programming is an increasingly important skill, whether you aspire to a career in software development, or in other fields.

Duke University

Andrew D. Hilton

Andrew D. Hilton

0 reddit posts

4 mentions

4 mentions

#30

Основы программирования на Python

Язык программирования Python является одним из самых простых в освоении и популярных языков программирования.

Язык программирования Python является одним из самых простых в освоении и популярных языков программирования.

National Research University Higher School of Economics

Густокашин Михаил Сергеевич

Густокашин Михаил Сергеевич

0 reddit posts

1 mentions

1 mentions

#31

Искусство разработки на современном C++
Specialization

В специализации преподаватели делятся своим многолетним опытом создания больших проектов на языке C++.

В специализации преподаватели делятся своим многолетним опытом создания больших проектов на языке C++.

Moscow Institute of Physics and Technology

Шишков Илья Иванович

Шишков Илья Иванович

0 reddit posts

1 mentions

1 mentions

#32

Shortest Paths Revisited, NP-Complete Problems and What To Do About Them

The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).

The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).

Stanford University

Tim Roughgarden

Tim Roughgarden

0 reddit posts

1 mentions

1 mentions