In 2012 with scientific research in Algebra, Vladimir won 1st place at the National contest in Russia, the Intel-Avangard, and became a finalist of the Intel ISEF.

After school, he enrolled for Bachelors at ITMO University for the programme of Applied Math and Programming. During his Bachelor's, he participated in several educational projects: in 2013 he was a coordinator of the national science fair for school students - BalticSEF; in 2014 he was a teacher in the LCME summer school, teaching two courses on maths. In the last years of his Bachelor’s, Vladimir entered the centre of additional higher education, Computer Science Center, for the programme of Software Engineering. In the end of summer of 2015, he completed a 3-month internship as a Software Developer.

After his Bachelor's, he started the Master’s at Harbour.Space University for the Data Science programme. There he joined Harbour.Space University team where he works as a software developer and also on the organisation of educational events and workshops.

The objectives in the course are to let the students:

- Get to know methods of descriptive statistics

- Be introduced to methods of inferential statistics

- Know how to calculate and generate statistics themselves using freely available statistical software

- Get to know basic principles of significance testing

- Get to know concrete statistical tests such as z-tests for 1 and 2 proportions, t-tests for 1 mean (paired differences) and 2 means and others

**SKILLS:**

- Algorithms & Data Structures

- Java

- Python

**DATE: **29 Apr - 17 May, 2019

**DURATION: **3** **Weeks

**LECTURES: **3 Hours per day

**LANGUAGE: **English

**LOCATION: **__Barcelona, Harbour.Space Campus__

**COURSE TYPE: **Offline

WHAT YOUWILL LEARN

COURSE OUTLINE

ABOUT VLADIMIR

BIBLIOGRAPHY

**HARBOUR.SPACE **

In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. We will discuss the methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance).

We will discuss methods of inferential statistics - methods that help us decide whether the patterns we see in our data are strong enough to draw conclusions about the underlying population we are interested in.

Also, we will go deeper into the matter of inferential statistics. Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population.

We will start by considering the basic principles of significance testing: the sampling and test statistic distribution, p-value, significance level, power and type I and type II errors. We will then consider a large number of statistical tests and techniques that help us make inferences for different types of data.

For those who are already familiar with statistical testing: We will look at t-tests for 1 mean (paired differences) and 2 means, the Chi-square test for independence, and among others non-parametric tests like Wilcoxon and Kruskal-Wallis.

VLADIMIRMAZIN

HARBOUR.SPACEUNIVERSITY

**DATE: **29 Apr – 17 May, 2019

**DURATION: **3 Weeks

**LECTURES: **3 Hours per day

**LANGUAGE: **English

**LOCATION: **__B____arcelona, Harbour.Space Campus__

**COURSE TYPE: **Offline

FOUNDATIONS

OF JAVA

**Session 2**

**Exploring data (cont.):**

Measures of central tendency and dispersion, Z-scores and example

**Session 3**

**Correlation and Regression:**

Correlation, Regression, Caveats examples

**Session 1**

**Introduction, Exploring data:**

About the course, How it’s organised, Data and visualisation

All rights reserved. 2018

**Session 4**

**Probability Distributions:**

Probability distributions, Mean and Variance of a Random Variable, The normal distribution, The Binomial distribution

We will discuss methods of inferential statistics - methods that help us decide whether the patterns we see in our data are strong enough to draw conclusions about the underlying population we are interested in.

Also, we will go deeper into the matter of inferential statistics. Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population.

We will start by considering the basic principles of significance testing: the sampling and test statistic distribution, p-value, significance level, power and type I and type II errors. We will then consider a large number of statistical tests and techniques that help us make inferences for different types of data.

For those who are already familiar with statistical testing: We will look at t-tests for 1 mean (paired differences) and 2 means, the Chi-square test for independence, and among others non-parametric tests like Wilcoxon and Kruskal-Wallis.

**BASICS OF STATISTICS**

**BASICS OF**

**STATISTICS**

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