Search result for Algorithms Online Courses & Certifications
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Algorithmic Toolbox
by Alexander S. Kulikov , Michael Levin , Neil Rhodes , Pavel Pevzner , Daniel M Kane- 4.6
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Approx. 39 hours to complete
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. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second). Programming Challenges Welcome!...
Discrete Optimization
by Professor Pascal Van Hentenryck , Dr. Carleton Coffrin- 4.8
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Approx. 65 hours to complete
Tired of solving Sudokus by hand? This class teaches you how to solve complex search problems with discrete optimization concepts and algorithms, including constraint programming, local search, and mixed-integer programming. Optimization technology is ubiquitous in our society. Optimization clears the day-ahead and real-time markets to deliver electricity to millions of people....
Mathematical Thinking in Computer Science
by Alexander S. Kulikov , Michael Levin , Владимир Подольский- 4.4
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Approx. 40 hours to complete
Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. In this course, we will learn the most important tools used in discrete mathematics: induction, recursion, logic, invariants, examples, optimality. We will use these tools to answer typical programming questions like: How can we be certain a solution exists?...
Graph Search, Shortest Paths, and Data Structures
by Tim Roughgarden- 4.8
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Approx. 15 hours to complete
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 network analysis). Week 1 Graph Search - Overview Breadth-First Search (BFS): The Basics...
Programming Fundamentals
by Andrew D. Hilton , Genevieve M. Lipp , Anne Bracy- 4.7
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Approx. 18 hours to complete
Programming is an increasingly important skill, whether you aspire to a career in software development, or in other fields. This course is the first in the specialization Introduction to Programming in C, but its lessons extend to any language you might want to learn. Introduction Why You Should Learn to Program...
Computer Vision Basics
by Radhakrishna Dasari , Junsong Yuan- 4.2
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Approx. 13 hours to complete
By the end of this course, learners will understand what computer vision is, as well as its mission of making computers see and interpret the world as humans do, by learning core concepts of the field and receiving an introduction to human vision capabilities. The course covers crucial elements that enable computer vision: digital signal processing, neuroscience and artificial intelligence....
Introduction to numerical analysis
by Evgeni Burovski- 4.7
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Approx. 18 hours to complete
Numerical computations historically play a crucial role in natural sciences and engineering. These days however, it’s not only traditional «hard sciences»: whether you do digital humanities or biotechnology, whether you design novel materials or build artificial intelligence systems, virtually any quantitative work involves some amount of numerical computing . We rely on libraries which package tried-and-tested, battle-hardened numerical primitives....
Competitive Programmer's Core Skills
by Alexander S. Kulikov , Alexander Logunov , Kirill Simonov , Aliaksei Tolstsikau- 4.6
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Approx. 32 hours to complete
During the course, you’ll learn everything needed to participate in real competitions — that’s the main goal. Along the way you’ll also gain useful skills for which competitive programmers are so highly valued by employers: ability to write efficient, reliable, and compact code, manage your time well when it’s limited, apply basic algorithmic ideas to real problems, etc....
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
by Tim Roughgarden- 4.8
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Approx. 15 hours to complete
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). Week 1 Application: Internet Routing Application: Sequence Alignment Introduction to Greedy Algorithms Application: Optimal Caching Problem Definition A Greedy Algorithm Correctness Proof - Part I...
Data Structures
by Alexander S. Kulikov , Michael Levin , Daniel M Kane , Neil Rhodes- 4.6
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Approx. 25 hours to complete
A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments....
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