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Since August 2026
Instructor since August 2026
Clases de programación para DAM, DAW y universidad | Java, Python, C y más
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From 29 € /h
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¿Estás estudiando DAM, DAW, Ingeniería Informática u otra formación tecnológica y se te está atravesando la programación?

Soy Nuria, profesora de informática con más de 10 años de experiencia docente y experiencia profesional en desarrollo y administración de sistemas.

Las clases son online, individuales y completamente adaptadas a tu temario, nivel y objetivos. Podemos empezar desde cero, preparar una asignatura o examen, trabajar sobre prácticas y entregas, resolver errores o avanzar con un proyecto.

Trabajo con distintos lenguajes y tecnologías, entre ellos **Java, Python, C, C#, PHP, JavaScript, SQL, OCaml** y otros que puedas utilizar en tu asignatura.

Podemos trabajar contenidos como:

* lógica de programación y resolución de problemas;
* algoritmos y estructuras de datos;
* programación orientada a objetos;
* programación funcional;
* funciones, clases, colecciones y excepciones;
* depuración y resolución de errores;
* acceso a bases de datos;
* desarrollo de aplicaciones;
* Git y control de versiones;
* prácticas, proyectos y preparación de exámenes.

Mi objetivo no es que memorices código ni copies soluciones, sino que aprendas a analizar un problema, dividirlo en partes, plantear una solución y entender por qué funciona.

Además de las clases, tendrás acceso a nuestra plataforma educativa con documentación propia, apuntes, ejercicios, ejemplos, prácticas y contenidos de nuestros cursos para continuar trabajando entre sesiones.
Extra information
Puedes traer tu propio temario, prácticas, ejercicios o proyectos. Adaptaremos las clases a lo que estés estudiando.
Location
location type icon
Online from Spain
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
Spanish
English
Availability of a typical week
(GMT -04:00)
New York
at teacher icon
Online via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
Do you want to learn Artificial Intelligence from scratch or do you need support with a subject, practice or project related to AI?

The classes are online, one-on-one, and fully tailored to your level and goals. We can work from the fundamentals to practical applications using Python, generative AI tools, language models, and APIs.

We can work on content such as:

fundamentals of Artificial Intelligence;
Python applied to AI and data processing;
data preparation, cleaning and analysis;
NumPy, pandas and data visualization;
Introduction to Machine Learning;
classification, regression and model evaluation;
Generative AI and Language Models (LLM);
use of ChatGPT, Gemini and other AI tools;
design and improvement of prompts;
consumption of AI model APIs;
task automation using AI;
AI integration in applications;
search and work with information and documents;
development of small projects and prototypes;
internships, projects and exam preparation.

The goal is not only to learn how to use AI tools, but to understand how they work, when to use them, and how to practically integrate them into your own projects.

We can start from scratch, work on the syllabus of your subject, or develop a specific application or project step by step.

In addition to the classes, you will have access to our educational platform with its own documentation, exercises, examples, practices and other resources to continue working between sessions.

Additional information for the student

You can bring your own syllabus, practical exercises, data, or project. We will adapt the classes to your prior knowledge and the objective you want to achieve.
Read more
Are you studying Web Development, Computer Engineering, or other technology-related fields and need help with web development?

The classes are online, one-on-one, and fully tailored to your syllabus, level, and goals. We can start from scratch, prepare for a subject or exam, solve practice problems, work on an assignment, or progress with a complete project.

We can work on content such as:

* HTML and CSS;
* JavaScript and client-side programming;
* PHP and backend development;
* frontend and backend;
* forms, sessions and authentication;
* consumption and creation of REST APIs;
* connection to databases and SQL;
* organization and architecture of web applications;
* Git and version control;
* debugging and error resolution;
* Frameworks and libraries according to your subject;
* application deployment;
* Development of internships and complete projects.

We can also work with the specific technologies, frameworks, or tools you are using in your training or project.

The classes are primarily hands-on. We'll analyze the problem, propose a solution, and work through the code so you understand what's happening and why.

My goal is not for you to copy a solution, but for you to develop the autonomy to analyze errors, organize an application, and tackle new problems on your own.

In addition to the classes, you will have access to our educational platform with its own documentation, notes, examples, exercises, practices and other resources to continue working between sessions.
Read more
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Most kids think coding is for "smart kids" or "future programmers."
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Why this is different:
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As a Franco-Belgian management teacher, I give Excel lessons with passion!
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Here are some key words that will be covered in my classes:
Scenario analysis, Year, Rounding, Today, Bdnb, Bdnbval, Bdsum, Search, Column, Copy/paste in values, Copy/paste with transposition, Consolidation, Date, Datedif, Determat, Dollar, Right, Righterg, Equiv, Esterror, Estna, Frequency, Filter (simple and advanced), Format of cells, Left, Large.Value, Printing of documents, Index, Indirect, Inversemat, Day, Weekday, Line, Matrix, Max, Maxa, Max.Si, Min , Mina, Mina.If, Formatting of cells and ranges, Month, Average, Average.If, Nb, Nb.If, Nbval, Naming of cells and ranges, No, Small.value, Product, Productmat, Protection of cells, Lookup (Lookup), Lookupv (VLookup), Lookuph (HLookup), If (If), If.Not.Disp, If.Conditions, Iferror, Sum, Sumproduct, Sum.If, Sum.If.Set, Substitute , Pivot tables, Sorting, Cell locking

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If you’ve ever felt that science and math are difficult, it’s probably because no one showed you how to think like a problem solver.
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Don't settle for anything less than excellence.
I am an Aerospace Engineer with a Master's degree in Quantum Physics and have completed Ph.D. work at the University of Cambridge in Computational Physics. Additionally, I have 4 years of experience developing MATLAB and possess deep programming skills in MATLAB/Simulink family, C/C++, Fortran, and Python.

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⭐⭐⭐⭐⭐

👨‍🎓 With 5 years of experience in distance and in-person teaching, I am a mathematics teacher specializing in tutoring and private lessons. I also teach physics, chemistry, and science subjects in general.

I hold a Master's degree in Operations Research (Applied Mathematics) and I have been teaching private lessons for over 5 years, mainly mathematics for middle and high school levels.

✏ I have taught students from different schools, whether public, private, following the French program (mission), Belgian, Swiss, Spanish (students from French-speaking or English-speaking Spanish schools) or American. In summary, all French or English programs.

✏ I support students from A to Z in all stages of their learning, using a simple, new generation and effective methodology: explanation of lessons, summary of lessons, application and deepening exercises, etc.

✏ I also prepare students for exams and competitions.

✏ I also support students with their homework (homework help).

✏ All my students have made extraordinary progress and achieved their goals, with grades of 16, 17, 18 or 19 out of 20.

Sessions usually take place as follows:

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4️⃣ Then I provide exams similar to what may be offered in class.

5️⃣ Upon request, I write a monthly report to keep parents informed of their child's level throughout the course.

I also adapt my methodology according to the needs of each student, which means that everyone has a personalized working method adapted to their needs!

I also offer crash courses for those preparing for the start of the school year, so that they start the year well prepared 💪 and with a head start on the program.🧠

💭 If you have any questions, don't hesitate to contact me ;)
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You will learn Systematic Reasoning & Logical Thinking which is a requirement for entering Computer Science program in many universities.
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• Predicate Logic: Predicates; Quantifiers; Tarski’s world and formal structures;
• Deduction: Valid arguments and proofs; Proofs in predicate logic

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Master Python with Personalized Courses

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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:

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Private Programming Lessons for you / your family / your company employees
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Deeper understanding, stronger results

• Lecturer at the American University AUC
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o Programming and computer courses for all educational levels (from primary to university)
o Microsoft Windows, Word, Excel, PowerPoint, Outlook, MS-Project
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o HTML, CSS, JavaScript, Angular
o Different database systems
o Data analysis using Excel
o Computer and Information Colleges Curricula
o Using artificial intelligence in life and work

• Master office applications to improve your job performance.
• Prepare yourself to work as a Front-End / Back-End / Full Stack Developer
• Theoretical and practical training for market requirements
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Experienced Teacher – Mathematics, Statistics & Computer Science

With more than 10 years of experience, I support pupils and students from middle school to university, as well as candidates for competitive exams (BCE, ECRICOME, TAGE MAGE, IAE MESSAGE, etc.).

Courses offered:

Mathematics (academic support, in-depth study, exam/competition preparation)
Applied Statistics & Probability
Computer science: Python, SQL, VBA, Data Mining
Methodological coaching (organization, efficiency, self-confidence)

Method: progressive and personalized approach, based on a diagnostic assessment, targeted exercises and regular monitoring to ensure lasting progress.

In-person or online teaching – individual or small group lessons.

Strengths:
More than 10 years of experience
Concrete results (students admitted to the best schools)
Clear, structured and motivating teaching

Prices adapted according to the level and the package chosen.
First free exchange to assess your needs.

Achieve your goals with quality support
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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.
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Бажаєш навчитися будувати власні розумні пристрої, зчитувати дані з датчиків та програмувати апаратне забезпечення? У цьому курсі ми поринемо у світ вбудованих систем (Embedded Systems).

Що ти вивчиш:

- Основи електроніки та проєктування схем.

- Програмування Arduino, ESP32 та STM32 на C/C++.

- Підключення датчиків (температури, звуку, руху) та виконавчих механізмів.

Практична реалізація: крок за кроком ми розроблятимемо твої власні проєкти у сферах робототехніки та IoT (інтернету речей).
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A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

2 — PROGRAMMING, ALGORITHMS, AND COMPUTER SCIENCE FOUNDATIONS
• Algorithmic thinking, problem decomposition, pseudocode, flowcharts, procedural programming, object-oriented programming, recursion, and modular program design
• Fundamental data structures including arrays, lists, stacks, queues, dictionaries/hash tables, sets, trees, graphs, and their appropriate use
• Searching, sorting, traversal, algorithm efficiency, computational complexity, Big-O notation, debugging, testing, code organization, and problem-solving strategies
• Practical programming exercises ranging from beginner problems to university-level algorithmic and computational challenges

3- DATA PREPARATION AND EXPLORATION
• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and data-quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation

4- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms

5- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation of results

6- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern or structure discovery
• Method selection, evaluation of data structure, and interpretation of results without predefined labels

7- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; hyperparameter optimization
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R2
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, feature selection, scaling, and regularization

8- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent neural networks, and Transformer foundations
• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

9- ARTIFICIAL INTELLIGENCE APPLICATIONS
• Natural language processing, text classification, embeddings, sentiment analysis, and foundations of language models
• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
• Recommendation systems, forecasting, anomaly detection, intelligent automation, and decision-support applications

10- GENERATIVE AI AND LARGE LANGUAGE MODELS
• Transformer architecture, tokens, embeddings, attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation
• Use of artificial-intelligence APIs, vector databases, document-retrieval systems, and structured AI-enabled workflows when relevant
• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

11- TOOLS AND LIBRARIES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
• Additional libraries may be introduced depending on the selected specialization and dataset

12- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• Complete projects covering data preparation, model development, evaluation, interpretation, and presentation of results
• University assignments, dissertations, theses, research projects, portfolio projects, technical interviews, and professional applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
B- PERSONALIZED TUTORING: LEARNING HOW TO REASON
Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

My lessons help you move beyond simply copying code or using models as “black boxes.” You will learn how to define the problem correctly, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret results rigorously and responsibly.

Each lesson is personalized according to your current level, mathematical background, programming experience, dataset, university work, research project, interview preparation, or professional objective. We begin by identifying your existing knowledge, software environment, expected outcomes, and main conceptual or technical difficulties. We then establish a structured learning plan.

The first lesson combines a discussion of your background, objectives, and tutoring needs; an initial assessment of your current knowledge; personalized planning and organization of future sessions; and a short trial lesson to determine the most effective learning approach.

A typical session may include conceptual explanation, development of mathematical intuition, live coding, guided implementation, model evaluation, technical problem solving, and a concise summary of the next steps.

You may work with your own dataset, university assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets suited to your level.

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.
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I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

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Teaching python to beginners!

In these classes, you will learn the basics of python programming, functions, lists, sets, and much more with practice assignments and assessments...

I have experience in teaching python to university peers.
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Contact Nuria
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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
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verified badge
As a Franco-Belgian management teacher, I give Excel lessons with passion!
Whether remotely or face-to-face, I offer many examples and exercises to accompany you.
I travel without problem throughout the region of Brussels and its surroundings, for lessons of at least 2 hours. For France, courses are only given remotely.

Here are some key words that will be covered in my classes:
Scenario analysis, Year, Rounding, Today, Bdnb, Bdnbval, Bdsum, Search, Column, Copy/paste in values, Copy/paste with transposition, Consolidation, Date, Datedif, Determat, Dollar, Right, Righterg, Equiv, Esterror, Estna, Frequency, Filter (simple and advanced), Format of cells, Left, Large.Value, Printing of documents, Index, Indirect, Inversemat, Day, Weekday, Line, Matrix, Max, Maxa, Max.Si, Min , Mina, Mina.If, Formatting of cells and ranges, Month, Average, Average.If, Nb, Nb.If, Nbval, Naming of cells and ranges, No, Small.value, Product, Productmat, Protection of cells, Lookup (Lookup), Lookupv (VLookup), Lookuph (HLookup), If (If), If.Not.Disp, If.Conditions, Iferror, Sum, Sumproduct, Sum.If, Sum.If.Set, Substitute , Pivot tables, Sorting, Cell locking

Do not hesitate to contact me to organize your lessons according to your needs and availability. Together, we will develop your Excel skills in an efficient and personalized way.
verified badge
If you’ve ever felt that science and math are difficult, it’s probably because no one showed you how to think like a problem solver.
In my classes, you’ll learn not just formulas or code but how to truly understand concepts, apply them, and build strong logical intuition.

I teach:
• 🔢 Mathematics: From algebra and calculus to applied problem-solving for real-world use.
• 💻 Computer Science: Coding fundamentals (Python, C++), algorithms, and logical thinking for beginners and intermediate learners.
• ⚛️ Physics: Mechanics, thermodynamics, and practical examples that make abstract ideas simple and visual.

As a Software Engineer and Master’s student in Engineering at Nagoya University, I bring both academic knowledge and hands-on experience from real projects. My teaching approach is interactive, visual, and deeply focused on understanding over memorization.

Let’s turn complex problems into clear, step-by-step insights — and make learning something you genuinely enjoy.
verified badge
Don't settle for anything less than excellence.
I am an Aerospace Engineer with a Master's degree in Quantum Physics and have completed Ph.D. work at the University of Cambridge in Computational Physics. Additionally, I have 4 years of experience developing MATLAB and possess deep programming skills in MATLAB/Simulink family, C/C++, Fortran, and Python.

With over 12 years of tutoring experience, I have successfully guided more than 50 students worldwide to achieve distinction in various fields. Consistent results are my priority, and I strive for excellence in all aspects of my teaching.

My lessons are customized to meet each student's unique needs and are designed to be engaging and insightful.

Whether you are at a school level or require advanced or professional-level instruction, I offer support in the following areas:
- Preparation for IB/IA, A-Levels, GCSE, University Entry, or equivalent.
- Experience in preparing students to access world-class schools and universities, including Cambridge University, Oxford, Ivy League and other top institutions in the UK and US.
- University levels (undergraduate and postgraduate).
- High school studies and diploma programs.
- Assistance with specific projects at a professional level, including job interview preparation.
- Extensive experience working with children.

Every lesson is meticulously planned in advance to ensure that it aligns with your goals and targets areas for improvement.
I prioritize a dynamic and interactive learning experience, with one-on-one sessions tailored to your individual requirements. Lessons will be conducted via webcam, enabling you to connect from anywhere.

I have a highly flexible schedule and can adapt to accommodate your needs.
If you have any questions about my teaching method, availability, or pricing, please don't hesitate to reach out. I am here to assist you and provide the support you need.
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⭐⭐⭐⭐⭐

👨‍🎓 With 5 years of experience in distance and in-person teaching, I am a mathematics teacher specializing in tutoring and private lessons. I also teach physics, chemistry, and science subjects in general.

I hold a Master's degree in Operations Research (Applied Mathematics) and I have been teaching private lessons for over 5 years, mainly mathematics for middle and high school levels.

✏ I have taught students from different schools, whether public, private, following the French program (mission), Belgian, Swiss, Spanish (students from French-speaking or English-speaking Spanish schools) or American. In summary, all French or English programs.

✏ I support students from A to Z in all stages of their learning, using a simple, new generation and effective methodology: explanation of lessons, summary of lessons, application and deepening exercises, etc.

✏ I also prepare students for exams and competitions.

✏ I also support students with their homework (homework help).

✏ All my students have made extraordinary progress and achieved their goals, with grades of 16, 17, 18 or 19 out of 20.

Sessions usually take place as follows:

1️⃣ The first sessions are mainly intended to assess the level of the student in order to determine the shortcomings noted.

2️⃣ Then we make a plan to fill those gaps: number of hours of work required, parts of the lessons to focus on, lots of training and development exercises, etc.

3️⃣ We make sure to stay up to date with the student's class teacher to track their progress and align our work with what is being taught in class.

4️⃣ Then I provide exams similar to what may be offered in class.

5️⃣ Upon request, I write a monthly report to keep parents informed of their child's level throughout the course.

I also adapt my methodology according to the needs of each student, which means that everyone has a personalized working method adapted to their needs!

I also offer crash courses for those preparing for the start of the school year, so that they start the year well prepared 💪 and with a head start on the program.🧠

💭 If you have any questions, don't hesitate to contact me ;)
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You will learn Systematic Reasoning & Logical Thinking which is a requirement for entering Computer Science program in many universities.
The book “Delftse Foundations of Computation” especially its second chapter will be the main source of our lesson, but other more in-depth books will be also covered if you want to improve even further on logical thinking.
The topics in our lesson include:
• Propositional Logic: Logical operators; Precedence rules; Logical equivalence; Implications in English; Exclusive or; Universal operators; Classifying propositions
• Boolean Algebra: Substitution laws
• Logic Circuits: Logic gates; Combining gates to create circuits; From circuits to propositions; Disjunctive Normal Form; Binary addition.
• Predicate Logic: Predicates; Quantifiers; Tarski’s world and formal structures;
• Deduction: Valid arguments and proofs; Proofs in predicate logic

If you have any additional questions before starting a class, please feel free to ask me. I am here to assist! :)
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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.
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This course is designed for anyone interested in learning data science using Python. It provides a hands-on introduction to fundamental data analysis tools such as NumPy, pandas, matplotlib, and seaborn. You'll learn how to manipulate datasets, create visualizations, and lay the foundations for statistical analysis and machine learning.

The course combines theory and practical exercises for effective, practical progress. No prior programming experience is necessary: we'll start with the basics to build solid, usable skills quickly.
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Private Programming Lessons for you / your family / your company employees
Programming Tutor – IGCSE & Computer Science Subjects
Deeper understanding, stronger results

• Lecturer at the American University AUC
• Over 20 years of experience in training students for government employees, oil companies (BP), food companies (Nestle), banks (CIB), and telecommunications companies (Vodafone).

• Teaching curricula, syllabuses, courses:
o IGCSE (Computer Science 0478, ICT 0417)
o Programming and computer courses for all educational levels (from primary to university)
o Microsoft Windows, Word, Excel, PowerPoint, Outlook, MS-Project
o Programming, C, C++, VB.NET, C#, Python, Database, SQL, MQL, VBA
o HTML, CSS, JavaScript, Angular
o Different database systems
o Data analysis using Excel
o Computer and Information Colleges Curricula
o Using artificial intelligence in life and work

• Master office applications to improve your job performance.
• Prepare yourself to work as a Front-End / Back-End / Full Stack Developer
• Theoretical and practical training for market requirements
• Don't miss out on technology. Lessons are designed for the elderly, in a simple and understandable way (use of computers and their programs, use of mobile phones, dealing with the Internet and social media).
• Lessons are available in person or online.
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Experienced Teacher – Mathematics, Statistics & Computer Science

With more than 10 years of experience, I support pupils and students from middle school to university, as well as candidates for competitive exams (BCE, ECRICOME, TAGE MAGE, IAE MESSAGE, etc.).

Courses offered:

Mathematics (academic support, in-depth study, exam/competition preparation)
Applied Statistics & Probability
Computer science: Python, SQL, VBA, Data Mining
Methodological coaching (organization, efficiency, self-confidence)

Method: progressive and personalized approach, based on a diagnostic assessment, targeted exercises and regular monitoring to ensure lasting progress.

In-person or online teaching – individual or small group lessons.

Strengths:
More than 10 years of experience
Concrete results (students admitted to the best schools)
Clear, structured and motivating teaching

Prices adapted according to the level and the package chosen.
First free exchange to assess your needs.

Achieve your goals with quality support
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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.
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Бажаєш навчитися будувати власні розумні пристрої, зчитувати дані з датчиків та програмувати апаратне забезпечення? У цьому курсі ми поринемо у світ вбудованих систем (Embedded Systems).

Що ти вивчиш:

- Основи електроніки та проєктування схем.

- Програмування Arduino, ESP32 та STM32 на C/C++.

- Підключення датчиків (температури, звуку, руху) та виконавчих механізмів.

Практична реалізація: крок за кроком ми розроблятимемо твої власні проєкти у сферах робототехніки та IoT (інтернету речей).
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A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

2 — PROGRAMMING, ALGORITHMS, AND COMPUTER SCIENCE FOUNDATIONS
• Algorithmic thinking, problem decomposition, pseudocode, flowcharts, procedural programming, object-oriented programming, recursion, and modular program design
• Fundamental data structures including arrays, lists, stacks, queues, dictionaries/hash tables, sets, trees, graphs, and their appropriate use
• Searching, sorting, traversal, algorithm efficiency, computational complexity, Big-O notation, debugging, testing, code organization, and problem-solving strategies
• Practical programming exercises ranging from beginner problems to university-level algorithmic and computational challenges

3- DATA PREPARATION AND EXPLORATION
• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and data-quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation

4- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms

5- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation of results

6- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern or structure discovery
• Method selection, evaluation of data structure, and interpretation of results without predefined labels

7- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; hyperparameter optimization
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R2
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, feature selection, scaling, and regularization

8- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent neural networks, and Transformer foundations
• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

9- ARTIFICIAL INTELLIGENCE APPLICATIONS
• Natural language processing, text classification, embeddings, sentiment analysis, and foundations of language models
• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
• Recommendation systems, forecasting, anomaly detection, intelligent automation, and decision-support applications

10- GENERATIVE AI AND LARGE LANGUAGE MODELS
• Transformer architecture, tokens, embeddings, attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation
• Use of artificial-intelligence APIs, vector databases, document-retrieval systems, and structured AI-enabled workflows when relevant
• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

11- TOOLS AND LIBRARIES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
• Additional libraries may be introduced depending on the selected specialization and dataset

12- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• Complete projects covering data preparation, model development, evaluation, interpretation, and presentation of results
• University assignments, dissertations, theses, research projects, portfolio projects, technical interviews, and professional applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results

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B- PERSONALIZED TUTORING: LEARNING HOW TO REASON
Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

My lessons help you move beyond simply copying code or using models as “black boxes.” You will learn how to define the problem correctly, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret results rigorously and responsibly.

Each lesson is personalized according to your current level, mathematical background, programming experience, dataset, university work, research project, interview preparation, or professional objective. We begin by identifying your existing knowledge, software environment, expected outcomes, and main conceptual or technical difficulties. We then establish a structured learning plan.

The first lesson combines a discussion of your background, objectives, and tutoring needs; an initial assessment of your current knowledge; personalized planning and organization of future sessions; and a short trial lesson to determine the most effective learning approach.

A typical session may include conceptual explanation, development of mathematical intuition, live coding, guided implementation, model evaluation, technical problem solving, and a concise summary of the next steps.

You may work with your own dataset, university assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets suited to your level.

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.
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I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

Topics include:
pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects
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Teaching python to beginners!

In these classes, you will learn the basics of python programming, functions, lists, sets, and much more with practice assignments and assessments...

I have experience in teaching python to university peers.
Good-fit Instructor Guarantee
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