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Since January 2026
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Python for Beginners – Structured and Practical Online Lessons
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From 30 $ /h
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Python for Beginners – Personal and Practical Online Lessons
Want to learn Python in a clear and structured way?
I offer online lessons tailored to your level, pace, and learning goals.
Whether you're an absolute beginner or already have some basic knowledge, we'll work step by step to build a strong programming foundation.
What will we cover?
Depending on your starting level, we can work on:
• Variables and data types
• Input and output
• If/else structures
• For and while loops
• Working with 1D and 2D lists
• Writing and using functions
• Working with files
• Basic error handling
• Programmatic thinking and problem solving
The content of the lessons is tailored to your goals, for example, for school, self-study, or exam preparation.
Lesson Structure
Each lesson consists of a combination of:
• Code analysis of sample programs
• Theory with concrete code examples
• Explanation of the underlying logic
• Exercises for independent practice
The goal is not just to learn what to type, but to understand why the code works and how to arrive at a solution yourself.
Who is this suitable for?
• Absolute beginners
• Students taking Python at school
• People who want to start programming
• Anyone looking for structured guidance
What can you expect?
• Personal guidance
• Explanation at your own pace
• Practical assignments
• Focus on understanding instead of speed
Not a fixed, standard course, but targeted guidance tailored to your learning process.
Extra information
Have Python installed and a code editor of your choice
Location
location type icon
Online from Netherlands
About Me
In my lessons, clarity and structure are key. I explain topics step by step and focus strongly on the why behind the material, so students don’t just follow instructions but truly understand what they are learning. There is always room for questions, repetition, and adjusting the pace to the student’s needs.

As a student with a solid IT background, I understand the challenges beginners often face. That’s why my teaching style is practical, patient, and beginner‐friendly, with a strong focus on creating a safe and comfortable learning environment. Lessons can be given in Dutch or English and are tailored to each student’s personal goals.
Education
I am currently a Cybersecurity student (Associate Degree).
Before this, I completed two IT programs: MBO‐3 IT Support and MBO‐4 Application Development, which provided me with a strong foundation in both technical skills and structured problem‐solving.
Experience / Qualifications
Through my studies, I have gained broad experience in IT fundamentals, programming, and cybersecurity methodologies. I focus on clear explanations and a structured, beginner‐friendly approach, with strong attention to ethics and professional practices. I am experienced in guiding students step by step and adapting lessons to individual learning goals and pace.
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Duration
60 minutes
The class is taught in
Dutch
English
Japanese
Reviews
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
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What will we cover?
Depending on your level, we can work on:
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• Links and images
• Introduction to CSS
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Lesson structure
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• Analysis of sample code
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• Exercises for independent practice
We'll work at a leisurely pace and build on what you've already learned.
For whom? • Absolute beginners
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The focus is on understanding basic grammar, vocabulary, and sentence structure, so you can read and form simple sentences.
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Depending on your pace, we'll work on:
• Hiragana and Katakana
• Basic vocabulary (JLPT N5 level)
• Elementary grammar
• Sentence structure
• Reading exercises
• Basic listening comprehension
• Simple conversation exercises
The emphasis is on structure and comprehension, not on rapid progress.
Lesson structure
Each lesson consists of:
• Grammar explanation with examples
• Application in simple sentences
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While adults are still debating whether kids should use AI, they are already using it.
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In this course, your child will discover:
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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

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• 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

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• 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

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• 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

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• 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.

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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.

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Python Level 1Workshop

**Course Description**

Want to learn programming from scratch? This beginner-friendly Python course introduces students to coding through interactive lessons, practical exercises, and fun mini-projects.

Students will learn how to write Python programs, work with different types of data, take user input, make decisions using conditions, and repeat actions using loops. Each concept is explained step by step with real-life examples and hands-on coding activities.

**What You Will Learn**

* **Lesson 1: Your First Python Program** — Learn the `print()` function, display messages, and create simple programs.
* **Lesson 2: Variables and Data Types** — Store and work with text, numbers, and other basic data.
* **Lesson 3: User Input and Calculations** — Build interactive programs that accept user input and perform calculations.
* **Lesson 4: Conditional Statements** — Use `if`, `elif`, and `else` to make programs respond to different situations.
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**Hands-On Projects**

Students will apply their learning by building beginner-friendly projects such as a calculator, a number-guessing game, and a Rock-Paper-Scissors game.

**Who Is This Course For?**

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**My Teaching Approach**

I explain concepts step by step, use relatable examples, and encourage students to write their own code instead of simply copying solutions. Lessons are adapted to each student's pace, with coding exercises and challenges to strengthen understanding.

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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).
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- Extensive experience working with children.

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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.

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* 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.

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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.
verified badge
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.
verified badge
I specialize in teaching ICT, computer science, and programming to help students develop essential digital skills for today's tech-driven world. My lessons are designed to guide you through both foundational concepts and more advanced topics, depending on your current level. I teach you very easy methods to understand complex parts of programming, breaking down difficult concepts into simple, digestible steps. Whether you’re a complete beginner looking to understand basic computer operations or an advanced learner aiming to master coding, networking, or system administration, I tailor each lesson to your needs. You will work on real-world projects, and I will provide exercises to reinforce learning and track your progress. Let's build your technical expertise together!
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🐍 Python Course – Learn to code and create your projects!

This course is for anyone who wants to:

✅ Learn Python from the beginning
✅ Strengthen their programming skills

📚 On the program:

Variables

Loops

Functions

Data structures

Practical projects for implementation

💡 How does the course work?

Clear explanations to understand the programming logic

Targeted exercises adapted to your level

Concrete projects to create your own applications

🎯 My goal:

Helping you understand the logic behind the code

Progress at your own pace

Create your own projects in Python and gain independence
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Primary School Teacher. I offer personalized guidance in developing lesson plans and learning activities adapted to current educational regulations. During our sessions, you will learn to structure and write a complete lesson plan, including specific competencies, assessment criteria, core knowledge, methodology, addressing diversity, evaluation, and learning situations. My goal is to help you understand each section so you can independently develop a coherent, rigorous, and high-quality lesson plan.

You will learn to design practical, creative proposals, developing the necessary skills to apply them in the classroom or in competitive examination processes.
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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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I am a certified computer science professor who helps graduates and students with exam retakes and competitions. I tutor preparatory classes (MPSI, MP, PSI, ECS, etc.) up to university level (Bachelor's & Master's in Science or Economics). My method is based on understanding the lessons, practicing correctly, organizing the concepts, and completing exercises and problems of your choice. Each session includes verbal exercises, methodological tips, and subsequent personalized advice. You will receive a video recording and an annotation in PDF format after each session. The online courses are conducted via Google Meet, 5 days a week, with flexible scheduling. I am available between sessions to answer questions. Contact me for an initial consultation.
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This course is designed for students and adolescents who want to build a strong beginner-friendly foundation in Computer Science.
Whether you're completely new to Computer Science or need help with a specific programming subject, the course can be customized to match your needs.
Need help with C++ or programming? You can provide me with your syllabus, course outline, or the topics you're studying, and I'll tailor the lessons around what you need to learn.
Learning with friends? Group lessons are also available, allowing you to learn together while following the same customized course.
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Python Level 1Workshop

**Course Description**

Want to learn programming from scratch? This beginner-friendly Python course introduces students to coding through interactive lessons, practical exercises, and fun mini-projects.

Students will learn how to write Python programs, work with different types of data, take user input, make decisions using conditions, and repeat actions using loops. Each concept is explained step by step with real-life examples and hands-on coding activities.

**What You Will Learn**

* **Lesson 1: Your First Python Program** — Learn the `print()` function, display messages, and create simple programs.
* **Lesson 2: Variables and Data Types** — Store and work with text, numbers, and other basic data.
* **Lesson 3: User Input and Calculations** — Build interactive programs that accept user input and perform calculations.
* **Lesson 4: Conditional Statements** — Use `if`, `elif`, and `else` to make programs respond to different situations.
* **Lesson 5: Loops and Mini-Projects** — Use loops to repeat actions and apply your skills in practical coding challenges.

**Hands-On Projects**

Students will apply their learning by building beginner-friendly projects such as a calculator, a number-guessing game, and a Rock-Paper-Scissors game.

**Who Is This Course For?**

* Children and teenagers aged 8–16.
* Complete beginners with no prior programming experience.
* Students who want to develop logical thinking, problem-solving, and computational skills.
* Learners who want to explore programming through practical projects.

**My Teaching Approach**

I explain concepts step by step, use relatable examples, and encourage students to write their own code instead of simply copying solutions. Lessons are adapted to each student's pace, with coding exercises and challenges to strengthen understanding.

**No prior coding experience is required.** Students need a computer and an internet connection to participate.

By the end of Level 1, students will have a solid foundation in Python basics and the confidence to start creating their own simple programs.
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