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Mathematical subjects for students of different levels

I am a postdoctoral researcher in the area of operations research and I propose the following classes:

The key to success in mathematics is to learn how to think outside-the-box. This valuable ability helps mathematicians to solve real problems in today’s world. This course helps to develop that crucial ability and, thus, to understand mathematics.

The beginner and intermediate classes focus on the overall understanding of school mathematics and, particularly, of the topics in
1) Algebra
2) Geometry
3) Introduction to probability

The advanced classes focus on particular fields in mathematics taught at universities (e.g., linear algebra, probability theory, optimisation etc.). I also train for the mathematics section of the GMAT exam.

Location

At teacher's location: St-Sulpice VD, centre, Saint-Sulpice, Switzerland
Online via webcam

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General info

Skills:

Age:

Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)

Student level:

Beginner
Intermediate
Advanced

Duration:

60 minutes
90 minutes
120 minutes

The class is taught in:

English, Russian, German

About Me

My name is Anna, I am a postdoctoral researcher in the field of Operations Research & Operations Management, focusing on theory and data-driven applications in the field of multi-stage decision-making under uncertainty. My professional background and practical skills are in the areas of operations research and statistics.

I earned my Ph.D. degree in Statistics and Operations Research at the University of Vienna in April 2014 with a dissertation devoted to theoretical and practical aspects of multi-stage stochastic programming, where the numerical solution of the optimization problem needed to be estimated by approximation of continuous-state stochastic processes with scenario trees. Before I joined the University of Vienna, I received my B.Sc. (2009) and M.Sc. (2011) degrees in Applied Mathematics and Physics at the Moscow Institute of Physics and Technology (National Research University).

Education

1) Ph.D. in Statistics and Operations Research (University of Vienna, Austria).
1) MSc in Applied Mathematics and Physics (Moscow Institute of Physics and Technology, Russia).
2) BSc in Applied Mathematics and Physics (Moscow Institute of Physics and Technology, Russia).

Experience / Qualifications

Machine Learning:

University course “Classification, Clustering, and Discrimination” for Master students: The course presents numerical methods used in the areas of classification, clustering, and discrimination. Rather than on classical statistical procedures, the focus is on modern techniques of machine learning which also enable applications to “big data” and business analytics. In particular, supervised and unsupervised learning algorithms are discussed, decision tree techniques are introduced, neural network methodology is outlined, and diverse clustering algorithms are presented.

Statistics:

Multiple university courses for Master students:
Recent courses are focusing on statistical methods for modeling non-linear dependencies in data. Copula models are introduced as a probabilistic way to derive general multivariate distributions based on marginal distributions for each of the random variables and on the information about the underlying dependence structure. Though it is often straightforward to fit marginals to the data, the estimation of a copula function requires complex up-scaling techniques, especially in high-dimensional cases. We introduce vine copulas as a way to take a different strength of interdependencies between random components into account and, further, we introduce hierarchical and ordered copulas as a way to approximate vine structure in very high-dimensional cases. Case studies in risk-management of extremes and in finance are presented.

Mathematics: Multiple university courses for Bachelor and Master students.

Software(MatLab):
The course presents efficient techniques for programming in MatLab. The software can be used for different kinds of "big data" applications. In particular, econometric and financial applications are considered.
This violin course proposes a solid foundation in learning one of the most rewarding instruments. I

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Availability of a typical week

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17  Monday at 17:00  Tuesday at 17:00  Wednesday at 17:00  Thursday at 17:00  Friday at 17:00  Saturday at 17:00  Sunday at 17:00
18  Monday at 18:00  Tuesday at 18:00  Wednesday at 18:00  Thursday at 18:00  Friday at 18:00  Saturday at 18:00  Sunday at 18:00
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from $113.93At teacher's location
from $113.93Online via webcam

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

Online reputation

  • Instructor since December 2019

Availability of a typical week

MonTueWedThuFriSatSun
7              
8              
9              
10              
11            Saturday at 11:00  Sunday at 11:00
12            Saturday at 12:00  Sunday at 12:00
13            Saturday at 13:00  Sunday at 13:00
14            Saturday at 14:00  Sunday at 14:00
15            Saturday at 15:00  Sunday at 15:00
16            Saturday at 16:00  Sunday at 16:00
17  Monday at 17:00  Tuesday at 17:00  Wednesday at 17:00  Thursday at 17:00  Friday at 17:00  Saturday at 17:00  Sunday at 17:00
18  Monday at 18:00  Tuesday at 18:00  Wednesday at 18:00  Thursday at 18:00  Friday at 18:00  Saturday at 18:00  Sunday at 18:00
19  Monday at 19:00  Tuesday at 19:00  Wednesday at 19:00  Thursday at 19:00  Friday at 19:00  Saturday at 19:00  Sunday at 19:00
20              
21              
22              
23              
from $113.93At teacher's location
from $113.93Online via webcam

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

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