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: ****1**8 May - 5 Jun, 2020

**DURATION: **3 Week

**LECTURES: **3 Hours per day

**LANGUAGE: **English

**LOCATION: **Barcelona, Harbour.Space Campus

**COURSE TYPE: **Offline

WHAT YOUWILL 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.

STANISLAVPROTASOV

**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 OUTLINE

**Session 1**

Number representation: IEEE-754

**Session 2**

Linear algebra in a nutshell

**Session 3**

Graphs

**Session 4**

Trees

MATHEMATICALFOUNDATIONS OFALGORITHMS

MATHEMATICALFOUNDATIONS OFALGORITHMS

BIBLIOGRAPHY

Discrete Mathematics and ItsApplications Seventh EditionBy Kenneth Rosen(McGraw-Hill Education, 2011)

Graham, R: Concrete Mathematics:Foundation for Computer SciencebyRonald L. Graham, Donald E. Knuth &Oren Patashnik(Addison Wesley, 1994)

**HARBOUR.SPACE **

Harbour.Space is a university created by entrepreneurs for entrepreneurs. We focus on meeting the demands of the future, while traditional education providers are too often stuck in the past.

We’re one of the only European institutions completely dedicated to technology, design and entrepreneurship, and our interdisciplinary courses are taught by some of today’s leading professionals. Our aim is not only to equip students with the knowledge to take on the real world, but to nurture, create and shape tomorrow’s tech superstars.

HARBOUR.SPACEUNIVERSITY