Michael Levin

Michael Levin serves as the Chief Data Scientist at Yandex Data Factory and is also an Associate Professor at the Computer Science Department of Higher School of Economics. He also teaches Algorithms and Data Structures at Yandex School of Data Analysis.

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Number Theory and Cryptography (Coursera)

We all learn numbers from the childhood. Some of us like to count, others hate it, but any person uses numbers everyday to buy things, pay for services, estimated time and necessary resources. People have been wondering about numbers’ properties for thousands of years. And for thousands of years [...]

Algorithms on Strings (Coursera)

World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. [...]

Algorithms on Graphs (Coursera)

If you have ever used a navigation service to find optimal route and estimate time to destination, you've used algorithms on graphs. Graphs arise in various real-world situations as there are road networks, computer networks and, most recently, social networks! If you're looking for the fastest time to get [...]

Data Structures (Coursera)

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 [...]

Algorithmic Toolbox (Coursera)

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. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem [...]

What is a Proof? (Coursera)

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 [...]

String Processing and Pattern Matching Algorithms (edX)

Learn about pattern matching and string processing algorithms and how they apply to interesting applications. The world and internet are full of textual information. We search for information using textual queries and read websites, books and e-mails.