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Learn Dynamic Programming online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
42 courses
This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow;…
Stanford Online
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).
MIT OpenCourseWare
This course covers concepts of computation used in analysis of engineering systems. It includes the following topics: data structures, relational database representations of engineering data, algorithms for the solution and optimization of engineering system designs (greedy, dynamic programming, br…
MIT OpenCourseWare
Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; greedy algorithms; amortized analysis; graph algorithms; and shortest paths. Advanced topics may…
Great Learning
In this course, you will understand the concepts of Dynamic Programming. You will start this course by understanding what Dynamic Programming is and the different problems that come under Dynamic Programming. After that, You will move to the Knapsack problem concept and see how Longest Common Subse…
MIT OpenCourseWare
This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow;…
DeepLearning.AI
In Course 2 of the Natural Language Processing Specialization, you will: a) Create a simple auto-correct algorithm using minimum edit distance and dynamic programming, b) Apply the Viterbi Algorithm for part-of-speech (POS) tagging, which is vital for computational linguistics, c) Write a better au…
This playlist is created for people who are looking to revise, or for people who want to cover the topics, and do not have much time on their hands for Interviews. This is an extracted playlist from the bigger one, which was created to teach you everything in depth, but that is for people who have…
The playlist aims to teach you Dynamic Programming in depth. The focus of the playlist is to cover all the concepts, and then follow it up with a lot of problems so that the concepts go into your head and stay there. The focus is on logic, so no matter in which language you code, you can easily con…
Stanford University
Welcome to the self paced course, Algorithms: Design and Analysis, Part 2! Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This course is an introduction to algorithms for learners with at least a little programming e…
The University of California, San Diego
Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.
The University of California, San Diego
Learn how to design algorithms, solve computational problems and implement solutions efficiently.
Technical programming interviews are challenging, but being able to do well is what lands you a job at a top tech company. Improve your interviewing skills by watching this mock full-length, real-world coding technical interview (OOP + dynamic programming) for a software engineering role. Interview…
The Georgia Institute of Technology
Delve into Pattern Matching algorithms from KMP to Rabin-Karp. Tackle essential algorithms that traverse the graph data structure like Dijkstra’s Shortest Path. Study algorithms that construct a Minimum Spanning Tree (MST) from a graph. Explore Dynamic Programming algorithms. Use the course visuali…
IBM
Build efficient programs by learning how to implement data structures using algorithmic techniques and solve various computational problems using the C++ programming language.
MIT OpenCourseWare
This course introduces the basic computational methods used to understand the cell on a molecular level. It covers subjects such as the sequence alignment algorithms: dynamic programming, hashing, suffix trees, and Gibbs sampling. Furthermore, it focuses on computational approaches to: genetic and…
MIT OpenCourseWare
The course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). We will consider optimal control of a dynamical system over both a finite and an infinite number of stages. This includes systems with finite or infinite sta…
Learn how to use Dynamic Programming in this course for beginners. It can help you solve complex programming problems, such as those often seen in programming interview questions about data structures and algorithms. This course was developed by Alvin Zablan from Coderbyte. Coderbyte is one of the…
University of California San Diego
This online 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. We will learn a lot of theory: how to sort data and how it helps for searching…
MIT OpenCourseWare
This is an intermediate algorithms course with an emphasis on teaching techniques for the design and analysis of efficient algorithms, emphasizing methods of application. Topics include divide-and-conquer, randomization, dynamic programming, greedy algorithms, incremental improvement, complexity, a…
