Statistics, math, data analysis (Matura / Abi + Uni) online

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From 54 € /h

Hi,
I'm Niko and I offer ONLINE tutoring in math, statistics, data analysis (with R and Python) and economics for all levels of education (including university). I have been teaching for some time and have looked after a total of over 100 pupils and students. The whole thing takes place via video chat and an interactive whiteboard. This is a tried and tested concept and has always worked excellently so far. So I'm looking forward to seeing you! :)

Since I have a good command of the R programming language, I can also help / consult with R on projects (e.g. homework or theses).

Location

Online from Switzerland

About Me

I have a Bachelor's degree in Mathematics and Economics and a Master's degree in Data Analytics. A few years ago, I discovered that I enjoy teaching students (especially in math, statistics and data analytics) and have been teaching diligently ever since. I have already given crash courses for the "Matheabitur" in Germany and lectures at the university, tutored lectures and have also given a lot of private tutoring in mathematical subjects. I also had the opportunity to teach math at a school in Nepal as part of my volunteer work. All these experiences have only motivated me so far. That's why I'm even more excited to be able to help you soon.

Education

I have three university degrees, two Bachelor degrees in Mathematics and Economics from the University of Heidelberg with a focus on Statistics, Probability Theory and Data Analytics. In addition, I have a Master's degree in Data Analytics.

Experience / Qualifications

I have many years of teaching experience at university and school level. I have already given crash courses for the mathematics baccalaureate, as well as lectures at the university and also through private tutoring already supervised a total of over 100 students

Age

Children (7-12 years old)

Teenagers (13-17 years old)

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Advanced

Duration

45 minutes

90 minutes

The class is taught in

German

English

Skills

Math

Statistics

Computer programming

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

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An experienced teacher at your disposal for:

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- Advice and supervision at the level of working methods.
- Recommended teaching methods.

Currently, I am doing my maths aggregation. I am already an electromechanical engineer, graduated as a senior technician in electronics and electrical engineering and who passed my bachelor's degree in mathematics with honors. I teach in different technical fields and especially mathematics, algebra and electronics.

At the level of my teaching methods, I use those that are advised pedagogically, I always try to explain and detail as much as possible the courses and I do not pass to the following stages until after making sure that the student understood what I explained.

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Preparation, help with exercises and follow-up of CNED students.
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What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
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- C and Java upon request
- MATLAB and R available for engineering/science students

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I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
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1.3 Differentiation (or derivative), slope, secant, tangent
1.4 Rules and theorems for differentiation, power rule, product rule, chain rule
1.5 Derivatives of exp, log, and trigonometric functions
1.6 Implicit differentiation and derivative of inverse functions
1.7 Rolle's theorem, mean value theorem, critical point, maximum/minimum of a function
1.8 First and second derivative tests, inflection points
1.9 Anti-derivative, indefinite integral, integration by substitution, integration by parts
1.10 Definite integral and its application (area between curves, application in physics)\
1.11 Optimization and linear differential equations

2. Linear Algebra:
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2.2 Equations for lines and planes, vector spaces, linear independence, span, basis, dimension
2.3 Linear transformations, coordinates, and representation of linear transformations by matrices
2.4 Matrix operations: matrix multiplication, transpose, determinant, inverse, and Hermitian conjugate
2.5 Systems of linear equations, Gaussian elimination
2.6 Eigenvalues and eigenvectors
2.7 Range, kernel, and rank-nullity theorem

and many more...

*Note that the sessions will be held online (via Discord/Zoom/Microsoft Teams).

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