Python Programming for Data Analysis, Data Science and OOP

From 18 £ /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.

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

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.

Zakaria

5.0

(3)

* This digital training aims to introduce you to the Scratch tool and through the game world, and gradually, to discover programming concepts such as loops, conditions or variables. It is aimed at anyone who is new to Scratch and who wants to create games and animations.

* Learning programming will allow students to develop their skills and will certainly allow them to meet the expectations of the future working world and emerging careers.

* In addition, learning programming allows the development of algebraic, algorithmic and computational thinking. Programming also helps to improve and develop students' sequencing ability, as well as their communication skills. Thus, there are several advantages to teaching programming, but the important thing is to remember that this learning teaches students that digital is not only for entertainment, but that it is possible to become creators. active and creative content.

Mohamed

5.0

(3)

As a highly qualified maths teacher, a graduate of the college of teachers and with 11 years of teaching experience in public high schools, I am happy to offer tutoring lessons in mathematics at home for students from level T and Common Core Sciences, TC Technological, 1st Baccalaureate Experimental Sciences and final of all the sectors (SVT-PC-SC.Math-L), as well as for the classes of 2nd and 1st general, Terminale specialty of the French system, as well than the 5th, 4th and 3rd levels of college.

My primary objective is to help students improve their level, deepen their knowledge, assimilate their lessons, fill their gaps and improve their skills in the discipline of mathematics. In addition, I am perfectly able to support them in the preparation of their exams and competitions for access to the Grandes Ecoles, and to provide them with homework help so that they can succeed in this subject.

With my advanced math skills and knowledge, I am confident that I can provide my students with effective tools and techniques to help them progress. My goal is to give them confidence and help them develop a passion for mathematics, a subject that can seem daunting at first, but can be exciting and rewarding if taught in an interesting and fun way.

By choosing my tutoring courses in mathematics, students can expect to receive individual attention and personalized help to overcome their difficulties and achieve their goals. My teaching approach is interactive and student-centered, which allows for a deeper understanding of mathematical concepts and a more practical application of acquired knowledge.

In summary, I am confident in my skills as a math teacher to help students of all levels progress and succeed in this demanding subject. I am convinced that my dynamic and stimulating teaching methods will help my students achieve their math goals and build a confidence that will follow them throughout their lives.

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.

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.

Sara

5.0

(3)

Do you dream of creating your own website but don't know where to start? 🙋‍♂️🙋‍♀️ This course is for you! This private tutoring program is designed for beginners, students, or professionals changing careers who want to master the essential basics of website creation. 📚

The Coaching Program includes:
HTML5: Structuring the content of a web page in a clean and semantic way.
CSS3: Style your pages, manage layout (Flexbox, Grid) and create responsive designs adapted to mobile devices.
JavaScript: Make your sites dynamic, manage user interactions (buttons, forms) and manipulate the DOM.
Practical Projects: Create your own projects from A to Z to build your portfolio.

💡 My 100% Personalized Methodology: The pace adapts completely to your strengths and difficulties.
Practical: 20% theory to 80% live coding and concrete exercises.
Continuous Monitoring: Sharing of resources, answer keys and mini-challenges between sessions.

See you soon to create your first website together! 😄👨‍🏫👩‍🏫

5.0

(3)

This course shows students how AI is the engine behind modern video games. It’s an engaging, project-based track ideal for advanced concepts in a fun, relatable environment.

Behavioral AI: Using simple visual programming environments (like Scratch or similar platforms) to program smarter Non-Player Characters (NPCs) that react realistically to the player's actions.

Generative Assets: Learning how game studios use generative AI tools to rapidly create textures, background stories, or simple game environments.

Interactive Storytelling: Exploring decision-tree logic and how AI can adapt game narratives based on player choices, making the game feel dynamic and intelligent.

SEN Alignment: The visual and immediate feedback loop of game design environments is highly effective for kinetic learners and helps maintain focus.

Aqsa

5.0

(3)

This lesson builds a solid foundation in numbers and variables by helping students understand how numbers are represented, how variables are used to express unknown values, and how they relate to real-world situations. Through clear explanations, guided examples, and practice activities, students develop algebraic thinking, logical reasoning, and confidence needed for advanced mathematics.

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

Ali

5.0

(3)

I offer one-to-one Programming tuition in Python, C, and C++, for GCSE Computer Science, A-Level Computing, and university students studying engineering, computer science, or related subjects. Lessons are available online or in person around Birmingham.

What I cover:

Python for beginners and intermediate learners
C and C++ programming
GCSE and A-Level Computer Science (all exam boards)
University coursework support, debugging help, and project guidance
Core concepts: variables, loops, functions, data structures, object-oriented programming, file handling, basic algorithms

How I teach:
I start by understanding exactly where you are — whether that's "I've never coded before" or "I'm stuck on a specific assignment." Then I build lessons around small, practical examples you can actually run and modify yourself. I'm patient with errors (everyone gets them), and I make sure you understand the why behind the code, not just how to copy it. For university students, I can also help with debugging, code reviews, and explaining tricky concepts in plain English.
If you or your child is preparing for exams, working on coursework, or just wants to finally feel comfortable with coding, I'd love to help.

Christaul

5.0

(3)

Do you want to learn to program or discover software development?
I offer programming courses focused on the essential basics of development with Python, one of the most widely used languages today.
In the program :
- Variables and data types;
- Conditions and loops;
- The functions;
- Data structures;
- The basics of object-oriented programming;
- Practical exercises and small projects.
The courses are suitable for students, secondary school students and adults wishing to acquire skills in computer development.

Ammar

5.0

(3)

A- SUJETS QUE VOUS POUVEZ EXPLORER ET MAÎTRISER :

1- FONDEMENTS DE PYTHON
• Variables, types de données, opérateurs, structures conditionnelles, boucles, fonctions, modules, fichiers, exceptions et programmation orientée objet
• Listes, tuples, dictionnaires, ensembles, compréhensions, débogage et écriture d’un code clair, réutilisable et bien structuré
• Jupyter Notebook, Anaconda, Visual Studio Code, environnements virtuels et gestion des packages

2- PRÉPARATION ET EXPLORATION DES DONNÉES
• NumPy et pandas pour importer, nettoyer, transformer, filtrer, regrouper, restructurer et fusionner les données
• Valeurs manquantes, doublons, valeurs aberrantes, formats incohérents, fuite de données (data leakage) et validation de la qualité des données
• Analyse exploratoire des données à l’aide de statistiques descriptives, Matplotlib, Seaborn et interprétation graphique

3- FONDEMENTS MATHÉMATIQUES
• Algèbre linéaire, vecteurs, matrices, dérivées, optimisation, probabilités et statistiques
• Fonctions de perte, gradients, mesures de distance, régularisation, vraisemblance et complexité des modèles
• Les concepts mathématiques sont expliqués en fonction du niveau de l’apprenant et des exigences des algorithmes sélectionnés

4- APPRENTISSAGE AUTOMATIQUE SUPERVISÉ
• Régression linéaire et polynomiale, régression logistique et modèles régularisés
• k plus proches voisins (k-nearest neighbours), arbres de décision, forêts aléatoires, gradient boosting, machines à vecteurs de support et classificateur naïf de Bayes
• Classification, régression, hypothèses des modèles, frontières de décision, importance des variables et interprétation des résultats

5- APPRENTISSAGE NON SUPERVISÉ
• Regroupement (clustering) par k-means, classification hiérarchique et méthodes fondées sur la densité
• Analyse en composantes principales, réduction de dimensionnalité, détection d’anomalies et découverte de structures ou de motifs
• Sélection des méthodes, évaluation de la structure des données et interprétation des résultats sans étiquettes prédéfinies

6- ÉVALUATION ET AMÉLIORATION DES MODÈLES
• Jeux d’entraînement, de validation et de test ; validation croisée ; optimisation des hyperparamètres
• Exactitude (accuracy), précision, rappel (recall), spécificité, score F1, ROC–AUC, matrices de confusion, MAE, MSE, RMSE et R2
• Sous-apprentissage, surapprentissage, compromis biais–variance, déséquilibre des classes, ingénierie des variables, sélection des variables, mise à l’échelle et régularisation

7- APPRENTISSAGE PROFOND
• Fondements des réseaux de neurones, fonctions d’activation, propagation avant, rétropropagation et descente de gradient
• Perceptrons multicouches, réseaux de neurones convolutifs, réseaux récurrents et fondements des Transformers
• TensorFlow, Keras ou PyTorch selon le projet et l’environnement de travail de l’apprenant

8- APPLICATIONS DE L’INTELLIGENCE ARTIFICIELLE
• Traitement automatique du langage naturel, classification de textes, plongements vectoriels (embeddings), analyse de sentiments et fondements des modèles de langage
• Vision par ordinateur, classification d’images, principes fondamentaux de la détection d’objets et prétraitement des images
• Systèmes de recommandation, prévision, détection d’anomalies, automatisation intelligente et applications d’aide à la décision

9- IA GÉNÉRATIVE ET GRANDS MODÈLES DE LANGAGE
• Architecture Transformer, tokens, embeddings, mécanismes d’attention, ingénierie des prompts, génération augmentée par récupération (Retrieval-Augmented Generation – RAG) et évaluation des modèles
• Utilisation d’API d’intelligence artificielle, de bases de données vectorielles, de systèmes de recherche documentaire et de flux de travail structurés utilisant l’IA lorsque cela est pertinent
• Fiabilité, hallucinations, biais, confidentialité, utilisation responsable et validation humaine appropriée

10- OUTILS ET BIBLIOTHÈQUES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras et PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel et Power BI lorsqu’ils sont utiles au projet
• Des bibliothèques supplémentaires peuvent être introduites en fonction de la spécialisation choisie et du jeu de données utilisé

11- PROJETS, RECHERCHE ET PRÉPARATION AUX ENTRETIENS
• Projets complets couvrant la préparation des données, le développement des modèles, leur évaluation, leur interprétation et la présentation des résultats
• Travaux universitaires, mémoires, thèses, projets de recherche, projets de portfolio, entretiens techniques et applications professionnelles
• Revue de code, débogage, documentation, reproductibilité, comparaison de modèles et communication des résultats

B- TUTORAT PERSONNALISÉ : APPRENDRE À RAISONNER
L’apprentissage automatique et l’intelligence artificielle deviennent beaucoup plus accessibles lorsque les mathématiques, les algorithmes, le code Python, les données et les applications concrètes sont clairement reliés entre eux.

Mes cours vous aident à aller au-delà de la simple copie de code ou de l’utilisation de modèles comme des « boîtes noires ». Vous apprendrez à définir correctement le problème, préparer les données, sélectionner un algorithme approprié, comprendre son fonctionnement, entraîner et évaluer le modèle, diagnostiquer les erreurs, améliorer ses performances et interpréter les résultats de manière rigoureuse et responsable.

Chaque cours est personnalisé en fonction de votre niveau actuel, de vos connaissances mathématiques, de votre expérience en programmation, de votre jeu de données, de votre travail universitaire, de votre projet de recherche, de votre préparation à un entretien ou de votre objectif professionnel. Nous commençons par identifier vos connaissances existantes, votre environnement logiciel, les résultats attendus ainsi que vos principales difficultés conceptuelles ou techniques. Nous établissons ensuite un plan d’apprentissage structuré.

Le premier cours gratuit combine une discussion portant sur votre parcours, vos objectifs et vos besoins en tutorat, une première évaluation de vos connaissances actuelles, une planification et une organisation personnalisées des séances, ainsi qu’un court cours d’essai afin de déterminer la méthode de travail la plus efficace.

Une séance type peut comprendre une explication conceptuelle, le développement de l’intuition mathématique, de la programmation en direct, une mise en œuvre guidée, l’évaluation des modèles, la résolution de problèmes techniques et une synthèse concise des prochaines étapes.

Vous pouvez travailler avec votre propre jeu de données, travail universitaire, projet de recherche ou problématique professionnelle, à condition que les informations confidentielles soient traitées de manière appropriée. Je peux également fournir des exemples structurés et des jeux de données adaptés à votre niveau.

Mon objectif n’est pas simplement de vous aider à exécuter un algorithme. Il est de vous permettre de comprendre pourquoi il est approprié, comment il apprend à partir des données, comment l’évaluer correctement, pourquoi il peut échouer et comment construire une solution fiable, interprétable et scientifiquement rigoureuse.