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Top Algorithms Courses

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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.
Princeton University
Kevin Wayne
1 reddit posts
385 mentions
#2
Algorithms Specialization
Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth.
Stanford University
Tim Roughgarden
1 reddit posts
189 mentions
#3
Fundamentals of Computing Specialization
This Specialization covers much of the material that first-year Computer Science students take at Rice University.
Rice University
John Greiner
1 reddit posts
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.
University of California San Diego
Alexander S. Kulikov
3 reddit posts
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.
Princeton University
Robert Sedgewick
0 reddit posts
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.
Duke University
Owen Astrachan
0 reddit posts
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...
University of California San Diego
Pavel Pevzner
1 reddit posts
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.
Duke University
Susan H. Rodger
1 reddit posts
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.
Stanford University
Daphne Koller
3 reddit posts
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.
Princeton University
Robert Sedgewick
0 reddit posts
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.
University of California San Diego
Alexander S. Kulikov
0 reddit posts
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...
University of Illinois at Urbana-Champaign
Wade Fagen-Ulmschneider
0 reddit posts
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.
Duke University
Andrew D. Hilton
2 reddit posts
27 mentions
#14
Mastering the Software Engineering Interview
You’ve hit a major milestone as a computer scientist and are becoming a capable programmer.
University of California San Diego
Mia Minnes
0 reddit posts
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.
Rice University
Luay Nakhleh
0 reddit posts
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).
Stanford University
Tim Roughgarden
1 reddit posts
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.
University of California San Diego
Pavel Pevzner
0 reddit posts
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.
The University of Edinburgh
Dr Areti Manataki
0 reddit posts
18 mentions
#19
Java Programming
Solving Problems with Software
Learn to code in Java and improve your programming and problem-solving skills.
Duke University
Owen Astrachan
0 reddit posts
25 mentions
#20
Algorithms for DNA Sequencing
We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data.
Johns Hopkins University
Ben Langmead, PhD
0 reddit posts
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.
The University of Tokyo
Takeo Igarashi
0 reddit posts
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.
Rice University
Scott Rixner
0 reddit posts
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.
University of California San Diego
Pavel Pevzner
0 reddit posts
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.
Rice University
Scott Rixner
0 reddit posts
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).
Stanford University
Tim Roughgarden
0 reddit posts
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.
Rice University
Luay Nakhleh
0 reddit posts
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...
Stanford University
Tim Roughgarden
0 reddit posts
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.
Stanford University
Daphne Koller
0 reddit posts
1 mentions
#29
Programming Fundamentals
Programming is an increasingly important skill, whether you aspire to a career in software development, or in other fields.
Duke University
Andrew D. Hilton
0 reddit posts
4 mentions
#30
Основы программирования на Python
Язык программирования Python является одним из самых простых в освоении и популярных языков программирования.
National Research University Higher School of Economics
Густокашин Михаил Сергеевич
0 reddit posts
1 mentions
#31
Искусство разработки на современном C++ Specialization
В специализации преподаватели делятся своим многолетним опытом создания больших проектов на языке C++.
Moscow Institute of Physics and Technology
Шишков Илья Иванович
0 reddit posts
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).
Stanford University
Tim Roughgarden
0 reddit posts
1 mentions