Python Programming for Data Analysis, Data Science and OOP

From 20 € /h

- Python Programming is currently the most utilized tool in the data analysis world. Its ease-of-use and wide variety of packages/libraries makes it a most valuable skill to have for a student wanting to get started in the world of data analysis and Object Oriented Programming.

- This course is geared towards beginners and intermediates who are interested in a hands-on approach to learning without neglecting the scientific background of the covered material, which will include the following:
* Introduction to Python Programming
* Understanding of OOP concepts and use-cases
* Crash course in statistical analysis concepts
* The usage of specified analysis libraries like Pandas and Numpy
* Introduction to Data science
* Neural Networks

Extra information

- Students should have their own PC/Laptop

Location

Online from Germany

About Me

I am an Automation Software Engineer working and studying in Germany for Masters degree in Industrial IT and Automation.

I have experience in industrial settings as an Automation Engineer with focus on SPS programming and development of Software tools using python. I also have experience in research settings working on data analysis, database systems and programmable boards (Raspberry Pi/Arduino, etc)

Education

Bachelors' Degree in Electrical Power and Machines Engineering- Alexandria University, Egypt
Masters' Degree in Industrial Automation and IT- TH Koeln, Germany

Experience / Qualifications

- Automation Engineer- Soulintec Encon
*Creation and development of automation infrastructure with Programmable Logic Controllers (SPS) and SCADA systems.
- Working Student Software - Aptiv
*I was responsible for development, maintenance and modification of software tools that offer assistance to software lifecycle tracking and also for reporting and metrics purposes
- Research Assistant - TH Koeln
* Worked on multiple research projects that include Indoor farming, Computer vision and data processing for industrial inspection of transparent objects.

Age

Children (7-12 years old)

Teenagers (13-17 years old)

Adults (18-64 years old)

Student level

Beginner

Intermediate

Duration

90 minutes

The class is taught in

English

Arabic

Skills

Computer programming

Numerical analysis

Software engineering

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

Gaëlle

5.0

(3)

Most kids think coding is for "smart kids" or "future programmers."
It's not. Coding is how real people solve real problems.
In this class, we skip the theory. Your child creates real things.

What they'll do:
✓ Build real projects in Scratch: a working game, an interactive animation, a story they coded
✓ Program virtual robots: solve real-world challenges (navigate a maze, automate a task, build a system)
✓ Create in Minecraft Education: design worlds, automate constructions, solve logic problems
✓ Experiment with different languages: not just learn "the right way," but understand that there are many ways to think about a problem
✓ Collaborate and share: work with other kids, get feedback, improve their work
✓ Develop logical thinking: not just for coding, but for anything: solving math problems, science challenges, real-world situations

Why this is different:
We don't teach syntax. We teach how programmers think.
Most children's coding courses say "here's the code, copy it." We teach "what problem are we trying to solve? How could we break it into steps? What options do we have?"
When your child learns to think like a programmer, they can learn any language afterward.

What they take home:
A portfolio of 3–4 completed, working projects. The ability to say "I built this." And the deep understanding that code is a tool to make real things happen.

Format: Online or Barcelona | 60–90 min sessions | Flexible pace, no prior experience needed
For curious 8-12 year olds who want to build.

5.0

(3)

Hello, I am a doctoral student in electrical engineering and associate professor in engineering sciences, experienced in the field of electrical engineering, I offer support courses in the subjects of engineering sciences (Electronics, automatics, electrical engineering, automation, programming).

Digital electronics
Analog electronic
electromagnetism (propagation of high frequency waves)
Automatic (continuous, sampled)
electrical engineering (transformers, electrical machines, switching power supply)
C / c ++ programming, Assembler, ARM, STM32
renewable energy (wind, PV)
engineering Sciences
RDM
Python,VHDL
PIC Microprocessor and Microcontroller
Signal processing and data acquisition
Engineering Sciences

These courses allow the student to get up to speed and regain confidence in all scientific subjects, just as they prepare him effectively for the Baccalaureate, the Preparatory Classes or various examinations of the engineering classes.

COURSE OBJECTIVES AND PEDAGOGICAL APPROACH

Resumption and deepening of fundamental concepts through exercises with course reminders.

Put the student in a situation of questioning and research.

Respond to individual issues and questions

Exercise training in order to achieve real mastery of the content.

Learn to build theoretical reasoning from observable facts or hypotheses.

Specific preparation for higher education requirements (in-depth content, increase in work capacity, enrichment of scientific background)

This educational approach is effective since it has often led me to interesting results with my students.

Associate professor provides support courses in electrical engineering

Matías

5.0

(3)

Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

This popularity means that Python is constantly evolving. It offers a wide range of tools and libraries, which are free and very varied.

As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

Beyond these general principles, there is no magic rule or method. Some approaches work with some students but not with others. Adaptation to individual needs is therefore the main objective of private lessons. So I will do my best to find what motivates and helps my student.

Adam

5.0

(3)

doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me

Aziz

5.0

(3)

Peace be upon you,
I am pleased to offer you support and reinforcement lessons in mathematics for the benefit of pupils and students, according to the level and need, in a simple, gradual and clear way.
My goal is not just to help the student complete the exercises or get a good grade, but to help him understand mathematics, gain confidence in himself, and learn how to think and search for the solution on his own.
During the lessons, I focus on:
• Review and explanation of lessons — Révision et explication des cours
• Addressing weaknesses — Remédiation des difficultés
• Simplification of mathematical concepts
• Solving exercises and problems — Résolution d'exercices et de problèmes
Preparing for assignments and exams — Préparation aux contrôles et aux examens
• Learn solution methods and ideas — Méthodes et astuces de résolution
• Error analysis and correction — Analyse et correction des erreurs
• Developing independence of thought — Développement de l'autonomie et du raisonnement
I don't prefer to give the solution directly. I first give the student a chance to try, think, and research, then I guide them step by step through appropriate hints and questions until they arrive at the solution themselves and understand the method.
Depending on the level, one can work on various mathematics lessons, including:
Number sets — Les ensembles de nombres
Fractions — Les fractions
Powers — Les puissances
Square roots — Les racines carrées
Literal arithmetic — Calcul littéral
Development and Factorisation
Notable identities
Equations
Inequalities
Systems of equations — Systèmes d'équations
Functions
Study of functions — Étude des fonctions
Limits
Continuity
Derivation
Primitives
Integral calculus
Differential equations — Équations différentielles
Numerical sequences — Suites numériques
Exponential function — Fonction exponentielle
logarithmic function
Trigonometry
Complex numbers
Plane geometry
Space engineering — Géométrie dans l'espace
Straight lines and planes in space — Droites et plans dans l'espace
Vectors — Vecteurs
Scalar product
Vector product
Analytical Geometry
Probabilities
Statistics
Counting — Dénombrement
Reasoning by regression
And other lessons according to the program and the student's level.
I also make sure to teach the student how to read the question, how to discover the important information, how to choose the appropriate method, and how to verify the correctness of his answer.
My goal is for mathematics to become an understandable, organized, and less difficult subject for the student, and for them to gradually move from waiting for the solution to being able to search for it themselves.
The number of students I follow up with is limited according to my available time, because I prefer the quality of follow-up and communication with each student over the large number.
Welcome to every student who wants to understand, progress and improve their level in mathematics.

Amin

5.0

(3)

Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
This course is built around real problems and real code. We skip the textbook formulas and go straight to applying statistics and data science the way professionals do: with Python (pandas, NumPy, scikit-learn, matplotlib) and R (RStudio).
What we cover, adapted to your level and goals:
- Descriptive and inferential statistics (the ones that actually matter)
- Data cleaning, exploration, and visualization
- Regression, classification, and intro to machine learning
- Time series and forecasting basics
- R for statistical analysis and academic research

Who this is for:
- University students in statistics, economics, engineering, or biology
- Professionals wanting to move into data analysis or data science
- Researchers who need to process and present data properly

I use Python and R professionally as a working engineer — everything I teach comes from real application, not just academic exercises.

Salah

5.0

(3)

Master Python with Personalized Courses

Discover the art of programming with Python courses tailor-made to meet your specific needs. Whether you are a beginner, intermediate or professional, my lessons are suitable for all levels.

Why Choose My Courses?

Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

Ongoing Support: Get unlimited email support for any questions you have between sessions.

As a Python expert, I have a passion for teaching and sharing my knowledge. My goal is to guide you effectively in your learning journey.

Book Your First Lesson:

Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.

Amine

5.0

(3)

Discover programming lessons suitable for children! With a fun and educational approach, my lessons allow young minds to dive into the fascinating world of programming. Provide your children with an enriching learning opportunity in a fun and stimulating environment.

Mohamed

5.0

(3)

Dive into the world of Python, one of the most powerful programming languages for Data Engineers and Data scientists. With hands-on projects, real-world examples, and engaging lessons, you'll not only learn the fundamentals of Python but also gain the confidence to tackle complex programming challenges.

Hassane

5.0

(3)

Description:
Get started with web development and learn how to create modern applications. This course takes you from the basics (HTML/CSS) to advanced concepts (security, APIs).

Goals :

Master HTML, CSS and JavaScript.
Understand the basics of authentication and web services.
Explore the concepts of security and load testing.
Course methods and format:

Video course: Creation of interactive mini-web projects.
Flexibility: Adapted to specific needs (beginner or advanced).
For who ?
Students, budding developers or professionals wishing to get started in the web.

Baia

5.0

(3)

I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work.

Topics include:
Python fundamentals through a finance lens (data structures, functions, control flow).
Working with financial data and datasets.
Performance benchmarking and writing efficient code.
Applying concepts from Hilpisch's Python for Finance.

Kevin

5.0

(3)

► EXPERT STATISTICS, DATA ANALYTICS, MACHINE LEARNING & AI TUTOR FROM SWITZERLAND
► UNIVERSITY, FOUNDATION, IB, A-LEVEL & INTERNATIONAL SCHOOL SUPPORT

I completed my Master’s degree in Business Information Systems at a Swiss University of Applied Sciences, where my academic background strongly combined mathematics, statistics, data analysis, analytical thinking and problem-solving. This technical and data-oriented foundation shaped the way I teach today: clearly, logically and with a strong focus on real understanding.

For many years, I have successfully supported students in Statistics, Data Analytics, Machine Learning and AI. My main focus is especially on Statistics — from basic descriptive statistics to advanced statistical methods, hypothesis testing, regression, probability distributions and interpretation of results.

I mainly use R for statistical analysis, data handling, visualisation and practical exercises. My goal is not only to help students calculate results, but to make sure they understand what the results mean and how to explain them correctly.

► STATISTICS, DATA ANALYTICS & AI SUPPORT

► STATISTICS & PROBABILITY
I help students understand descriptive statistics, probability, random variables, distributions, sampling, confidence intervals, hypothesis testing, p-values, correlation, regression and statistical interpretation. My lessons focus on explaining the logic behind each method, not just applying formulas.

► APPLIED STATISTICS WITH R
I support students in using R for statistical analysis, data cleaning, visualisation, hypothesis testing, regression models and interpretation of outputs. Students learn how to connect theory, calculation, code and real meaning step by step.

► QUANTITATIVE METHODS & RESEARCH STATISTICS
I help students with statistical methods used in business, economics, psychology, social sciences, science and university research. This includes choosing the correct test, understanding assumptions, interpreting results and presenting findings clearly.

► DATA ANALYTICS & DATA SCIENCE
I support students with data preparation, exploratory data analysis, visualisation, dashboards, summary statistics and practical interpretation. The focus is always on understanding the data and drawing meaningful conclusions.

► MACHINE LEARNING & AI FOUNDATIONS
For students working with modern data topics, I also provide support in the foundations of Machine Learning and AI, including regression, classification, clustering, model evaluation and practical applications. These topics are explained from a statistical point of view, so students understand the logic behind the models.

► UNIVERSITY, FOUNDATION & INTERNATIONAL COURSES
I support students in Statistics, Data Analytics, Business Analytics, Quantitative Methods, Econometrics, Research Methods and technical modules. I help with exam preparation, assignments, projects and practical data analysis tasks.

► HOW I TEACH

► I FOCUS ON REAL STATISTICAL UNDERSTANDING.
Statistics becomes much easier when students understand why a method is used, what the result means and how to interpret it correctly.

► I EXPLAIN FORMULAS STEP BY STEP.
Difficult formulas, tests and models are broken down into simple, logical parts so students can follow the reasoning clearly.

► I CONNECT THEORY WITH R PRACTICE.
Students learn not only the statistical theory, but also how to apply it in R, read the output and explain the result in proper academic language.

► I HELP STUDENTS CHOOSE THE RIGHT METHOD.
Many students struggle with deciding whether to use a t-test, chi-square test, ANOVA, regression or another method. I teach students how to recognise the correct approach from the question or dataset.

► I TRAIN INTERPRETATION AND EXAM TECHNIQUE.
Students learn how to structure statistical answers, write clear conclusions, explain p-values, interpret confidence intervals and present results professionally.

► I ADAPT EVERY LESSON TO THE STUDENT.
Some students need help with theory, others with R coding, assignments, research projects or exam preparation. I adjust every lesson to the student’s exact course, level and goals.

► YEARS OF EXPERIENCE WITH STATISTICS, DATA & UNIVERSITY STUDENTS

Over the years, I have successfully supported students from demanding academic programmes, helping them strengthen their statistical understanding, improve their analytical thinking and achieve excellent progress in Statistics, Data Analytics, Machine Learning and AI.

► ONLINE LESSONS

► Interactive whiteboard
► Clear digital notes
► Step-by-step statistical explanations
► R support for data analysis
► Exam preparation
► Assignment and project guidance
► Practical examples with real datasets
► Focused one-to-one support from Switzerland

► MY GOAL

My goal is not only to help students pass exams or complete assignments, but to help them truly understand Statistics. With the right guidance, statistical methods become logical, practical and much easier to apply.

► SUBJECTS: Statistics, Probability, Data Analytics, Data Science, Machine Learning, AI, Quantitative Methods, Research Methods, Econometrics
► MAIN TOOL: R
► LEVELS: International School, IB, A-Level, Foundation Courses, University Modules, Professional Training
► FORMAT: Online tutoring from Switzerland
► FOCUS: Statistical understanding, R practice, interpretation, exam preparation, assignments, projects and long-term analytical confidence.

Aafaq

5.0

(3)

Calculus I, the first course in this extensive mathematics curriculum, teaches students the foundational ideas of limits, derivatives, and how to apply them to real-world issues including rates of change and optimization. Calculus III, which builds on this basis, introduces partial derivatives, multiple integrals, and vector calculus, extending these concepts into several dimensions. When taken as a whole, these calculus courses build the solid analytical foundation and spatial thinking abilities needed for further study in applied mathematics, science, and engineering.

Students study Number Theory concurrently, exploring the complex patterns and characteristics of integers, such as primes, modular arithmetic, divisibility, and the classical theorems that form the basis of much of contemporary computer science and encryption. In addition to this theoretical emphasis, the Numerical Methods course gives students useful computational tools to help them approximate solutions to challenging mathematical problems that are impossible to solve analytically. Students are prepared for a variety of jobs in mathematics, engineering, technology, and other fields by this program, which blends strong theoretical knowledge with algorithmic problem-solving abilities.

Farouk

5.0

(3)

These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

Object-Oriented Programming is often perceived as complex or abstract.

My goal is simple: to make it logical, concrete, and immediately applicable.

🎯 Training Objectives

Upon completion of this training, you will be able to:

Understanding what Object-Oriented Programming really is (and when to use it)
Create and manipulate objects in JavaScript in a clean and efficient way
Use ES6 classes, constructors, and methods with confidence
Mastering this, the prototype, and the instantiation logic
Apply encapsulation, inheritance, and polymorphism without confusion
Avoiding common mistakes made by OOP beginners
Structure your JavaScript code like a professional developer

📖 Training Plan – Object-Oriented Programming in JavaScript
1. Introduction to Object-Oriented Programming 🧠
Understanding the concept, objectives and benefits of OOP.
2. Procedural Programming vs. OOP
Why unstructured code quickly becomes unmanageable.
3. Objects in JavaScript
Properties, methods and representation of the real world.
4. The keyword this
Understanding the execution context (often poorly understood).
5. Limitations of simple objects
Why duplicating code is a bad idea.
6. Constructive functions
Create multiple objects from the same model.
7. The keyword new
What it's actually doing under the hood.
8. The prototype
Sharing methods and memory optimization.
9. ES6 Classes
Modern syntax and best practices.
10. The builder
Proper initialization of objects.
11. Data Encapsulation
Protect the internal state of objects.
12. Inheritance between classes
Reusing code intelligently.
13. The keyword super
Communication between parent and child in the classroom.
14. Polymorphism
The same behavior, several forms.
15. Composition vs. Inheritance
Choosing the right architecture.
16. Best practices in OOP
Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

🛠️ Teaching method: Understand before writing

This training program is based on a progressive and pragmatic approach:
Clear and illustrated explanations
Concrete examples from real projects
Simple but effective exercises
Constant questioning to avoid rote learning
Adaptation to the learner's level and pace
Here, we don't "recite OOP" — we understand it.

🚀 Learner's result

At the end of the training, you will not only know how to write a JavaScript class.
You will know:

1- Why does it exist?
2- When to use it
3- and when not to use it

You will leave with:
a solid understanding of OOP
a cleaner and more professional code
an ideal foundation for learning React, Node.js or any other modern framework

Yassine

5.0

(3)

Professeur agrégé de informatique, j’aide élèves et étudiants à réussir examens et concours. J’interviens aux classes préparatoires (MPSI, MP, PSI, ECS...) et jusqu’à l’université (Licence & Master en sciences ou économie). Ma méthode : comprendre le cours, pratiquer avec rigueur, structurer le raisonnement et ha des exercices et problèmes bien choisis. Chaque séance inclut exercices ciblés, conseils méthodologiques, et suivi personnalisé. Vous recevez un enregistrement vidéo plus un PDF annoté après chaque cours. Cours en ligne via Google Meet, 5 jours sur 7, avec flexibilité horaire. Je reste joignable entre les séances pour répondre aux questions. Contactez-moi pour un premier échange.