RESERVE MY SPOT
Stanislav Protasov graduated from the Computer Science department of Voronezh State University in 2009. In 2013 he defended his PhD thesis devoted to computer vision algorithms. While doing his research he was also working as a software developer in DHL, Parallels, DataArt and Yandex. He delivered labs and lectures in Voronezh State University, National Research University Higher School of Economics (HSE), Moscow Institute of Physics and Technology (MIPT) and Skoltech.
Since 2020 he works as an assistant professor in the Machine Learning and Knowledge Representation lab of Innopolis University.
The major objective of the course is to give students strong connections between mathematical tools and their future professional tasks. This objective splits into smaller goals students will achieve during this course. After the course students will:
Understand:
-Most of mathematical notation used in computer science papers
-Number representation in most programming languages
-Major terms of linear algebra for computations
-Big O notation
Know:
-Method of graph and tree representation in memory
-Recursion idea, pros and cons
-Approaches to discrete optimization
-Computational models (RAM model, FSM)
Apply:
-Knowledge on number representation to computational tasks
-Linear algebra basics to solving graph problems
-Write mathematical formulas with LaTeX
-Big O analysis for algorithm time complexity estimation
-Use numpy for computations
-Use jupyter notebooks, jupyter lab and Google Colab
-Use github
SKILLS:
- .NET
- JavaScript
- Full-stack Development
- Applied Mathematics
- GIT
- ASP.NET MVC
DATE: 18 May - 5 Jun, 2020
DURATION: 3 Week
LECTURES: 3 Hours per day
LANGUAGE: English
LOCATION: Barcelona, Harbour.Space Campus
COURSE TYPE: Offline
WHAT YOU WILL LEARN
ABOUT STANISLAV
Whatever mathematical discipline you are studying, it is always important to build connections between tools you learn and real problems you can address with these tools. The course you are reading about always keeps applications in focus. During this course we will learn selected topics of discrete mathematics, linear algebra and programming, which are meant to be essential knowledge for future data scientists, programmers, software engineers, and other IT specialists. We will consider each topic with respect to its application to computational and algorithmic tasks.
STANISLAV PROTASOV
DATE: 18 May – 5 Jun, 2020
DURATION: 3 Weeks
LECTURES: 3 Hours per day
LANGUAGE: English
LOCATION: Barcelona, Harbour.Space Campus
COURSE TYPE: Offline
All rights reserved. 2020
COURSE OUTLINESession 1
Number representation: IEEE-754
Session 2
Linear algebra in a nutshell
Session 3
Graphs
Session 4
Trees
MATHEMATICAL FOUNDATIONS OF ALGORITHMS
MATHEMATICAL FOUNDATIONS OF ALGORITHMS
BIBLIOGRAPHY
Discrete Mathematics and Its Applications Seventh Edition By Kenneth Rosen (McGraw-Hill Education, 2011)
Graham, R: Concrete Mathematics: Foundation for Computer Science by Ronald L. Graham, Donald E. Knuth & Oren Patashnik (Addison Wesley, 1994)
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