Search result for Courses taught by Alexander S. Kulikov
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Data Structures Fundamentals
by Daniel Kane , Alexander S. Kulikov , Michael Levin , Neil Rhodes- 0.0
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6 Weeks
Learn about data structures that are used in computational thinking – both basic and advanced. A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments....
$99
Algorithmic Design and Techniques
by Pavel Pevzner , Daniel Kane , Alexander S. Kulikov , Michael Levin- 0.0
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6 Weeks
Learn how to design algorithms, solve computational problems and implement solutions efficiently. In this course, part of the Algorithms and Data Structures MicroMasters program, you will learn basic algorithmic techniques and ideas for computational problems, which arise in practical applications such as sorting and searching, divide and conquer, greedy algorithms and dynamic programming....
$99
Graph Algorithms
by Daniel Kane , Alexander S. Kulikov , Michael Levin- 0.0
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6 Weeks
Learn how to use algorithms to explore graphs, compute shortest distance, min spanning tree, and connected components. If you have ever used a navigation service to find the optimal route and estimate time to destination, you've used algorithms on graphs. We will also talk about shortest paths algorithms. Graph exploration and decomposition into connected components...
$150
NP-Complete Problems
by Daniel Kane , Alexander S. Kulikov- 0.0
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3 Weeks
Learn about NP-complete problems, known as hard problems that can’t be solved efficiently, and practice solving them using algorithmic techniques. Step into the area of more complex problems and learn advanced algorithms to help solve them. You will practice solving large instances of some of these problems despite their hardness using very efficient specialized software and algorithmic techniques including:...
$150
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!...
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?...
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....
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....
Introduction to Graph Theory
by Alexander S. Kulikov- 4.5
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Approx. 21 hours to complete
We invite you to a fascinating journey into Graph Theory — an area which connects the elegance of painting and the rigor of mathematics; is simple, but not unsophisticated. Graph Theory gives us, both an easy way to pictorially represent many major mathematical results, and insights into the deep theories behind them....
Computational Geometry
by Alexander S. Kulikov , Aliaksei Tolstsikau , Kira Vyatkina- 3.9
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Approx. 19 hours to complete
This course represents an introduction to computational geometry – a branch of algorithm theory that aims at solving problems about geometric objects. Its application areas include computer graphics, computer-aided design and geographic information systems, robotics, and many others. Point inclusion in a polygon 1. 1 Introduction 1. 2 Problem statement 1....
