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Since February 2023
Instructor since February 2023
Python - from complete beginner to SDE intern level
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From 45 € /h
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Being able to program and code has become essential in the modern world. Too often schools' education programs don't offer good quality programming courses, and this might stop young people from discovering new possibilities for their future. Python is one of the most used and versatile programming languages, as well as the best to start grasping the basic concepts of coding.

In this course I will guide from the first steps up to acquiring advanced coding skills. Choose your level and book the first lesson.

Beginner:
- Introduction to Coding
- Basic python types and structures (string, list, ...)
- Concept of functions
- Input and output to console and text file

Example Output:
You will be able to create small console app such as an interactive calculator or a simple pre-programmed chatbot.

Intermediate:
- More complex data structures (matrices, linked lists, graphs, trees...)
- Concept of classes
- Using external libraries
- Algorithms for sorting and information retrieval
- Complexity of code (time and space required)

Example Output:
This will give you a broad set of tools to do a large amount of tasks. You will be able to solve complex Sudokus in less than a second as well as store complex types of data as objects. You will be able to create games, from very simple ones such as tic-tac-toe to more complex ones such Flappy Birds (creativity is the only limit).
Note: the course is not focused on games, but to give you the basic tools.

Advanced:
This course can be customized according to the students interest. Possible options are:
- Machine Learning (such as training a neural network how to distinguish dogs or cats)
- Navigation algorithms (how to find the shortest path to the goal in a map)
- Others directions can be discussed (feel free to text me if you have any question)

Good luck, and see you soon :)
Extra information
You will need a laptop to work on and a good internet connection.
Location
location type icon
Online from Switzerland
About Me
Hi,

Are you ready to take a fun and engaging course with me?
My name is Matteo, an enthusiastic Robotics student, with broad experience both in academy and industry, check the education section if you want to know more. :)

Everything looks hard at first without the proper introduction. My goal is to give you the tools to understand complex topics, in a seamless and interesting way.
Education
- Thesis at Stanford University
- Intern Amazon : Software Engineer
- MSc at ETH Zurich : Robotics and AI
- Bachelor's at University of Rome, Sapienza : Software and Automation Engineer
Experience / Qualifications
I have 4 years of tutoring experience. In this time I had the chance to work with 9 amazing students, from middle school school up to last year of university.
I am proud and happy to have helped them achieving their goals while fun in the meantime.
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
English
Italian
Availability of a typical week
(GMT -05:00)
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
Learning math can be tough and frustrating if the teacher is not very clear.
The goal of this class will be helping you out understanding in a deeper way how math works and preparing you to school tests. The lessons will be done online and I will follow you step-by-step, leaving you space to ask questions and clarify any doubt.
Read more
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Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

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Master Python with Personalized Courses

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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.

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Do you want to learn programming but don't know where to start? Are you a beginner looking for clear explanations, or do you want to improve your coding skills with personalized support?

This private tutoring program is designed to help you master Python, one of the most versatile and easy-to-learn programming languages. Through a step-by-step approach, interactive exercises, and hands-on projects, you'll gain the confidence and skills to write code effectively and solve real-world problems.

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This interactive, hands-on learning experience ensures you understand Python while having fun coding!

📚 What Will You Learn?
This program covers everything you need to become comfortable with programming in Python:

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✅ Self-taught – If you want to add Python to your skillset, this course offers you structured support.
✅ Professionals and people in retraining – Python is a sought-after skill in data science, automation and web development.
✅ Tech Enthusiasts – Curious to learn code? This course makes learning Python both fun and useful.

🚀 Ready to Embark on Your Python Adventure?
Join the "🐍 Personalized Private Lessons – 💻 Learn to Code and Program in Python!"
Gain the skills and confidence to write clean, efficient, and powerful code.

Sign up today and take your first steps into the exciting world of Python programming! 🔥
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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.

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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.

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You have a kid that's interested in programming?? Set up a class for him with me. Aya a software engineer turned teacher. I was a software engineer for 3 years before I joined the teaching industry and I currently teach computer science in Chichester College in United Kingdom. I want to advocate for computer science and help familiarise kids at a young age with programming in Python.

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Learn Python by building something you’ll actually use

Ever wanted to code but had no idea where to begin? You’re in the right place. In these relaxed, one-on-one lessons, you’ll go from zero to writing real programs, with no experience required.

Together, we’ll choose a project that fits your interests. Maybe it’s a video game you want to build or a quiz to challenge your friends, a chart built from your own spreadsheet, or a script that takes over a boring, repetitive task. Along the way, you’ll pick up the essentials (variables, loops, functions) and learn to read error messages without panic, so you can change your code with confidence.

Where you can go next

AI-assisted coding: Use tools like ChatGPT to brainstorm, decode errors, and improve your code, while learning to test its suggestions and explain how the final result works.
Machine learning: Train a simple model on a real dataset and see how well it predicts.
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Your instructor

I’m an engineer with a master’s degree from Nagoya University and research experience in applied AI and computer vision. I explain every concept in plain language, then give you time to try it yourself with live feedback, so you’re never stuck alone.

Ready to start?

Send me a quick message and let's do your first coding project together.
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Contact Matteo
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I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

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Learn to code with method and logic
Whether it's to succeed in the NSI (Digital Sciences and Technology) specialization in high school, design personal projects, or prepare for higher scientific studies, mastering code relies on solid algorithmic thinking. I help students understand the structure of programming languages and the logic of data.

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What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
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I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
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verified badge
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.

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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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Do you want to learn programming but don't know where to start? Are you a beginner looking for clear explanations, or do you want to improve your coding skills with personalized support?

This private tutoring program is designed to help you master Python, one of the most versatile and easy-to-learn programming languages. Through a step-by-step approach, interactive exercises, and hands-on projects, you'll gain the confidence and skills to write code effectively and solve real-world problems.

💡 Why Choose this Program?
With these personalized courses, you will:
-
🚀 Learn at your own pace – Whether you’re a complete beginner or want to refine your skills, lessons adapt to your level.
🎯 Master the fundamentals – Understand key concepts like variables, loops, functions, and object-oriented programming.
🏗️ Complete hands-on projects – Work on real-world coding exercises, from simple scripts to mini-apps.
🐍 Develop problem-solving skills – Learn how to break down complex tasks and write efficient code.
🎓 Prepare for exams, jobs or personal projects – Whether you are a student, professional or enthusiast, Python is an essential skill.
💻 Get live support – Get real-time feedback, coding tips, and answers to your questions.
This interactive, hands-on learning experience ensures you understand Python while having fun coding!

📚 What Will You Learn?
This program covers everything you need to become comfortable with programming in Python:

✅ Python Basics (Great for Beginners)
Introduction to Python and installation of the development environment 🖥️
Variables, data types and user input 🔢
Operators and expressions 🧮
Conditional structures (if-else) and loops (for, while) 🔄
Writing and calling functions 🏗️
🚀 Intermediate Concepts (To Go Further)
Lists, Tuples, Dictionaries – Understanding Data Structures 📊
File Management – Reading and Writing Files 📄
Exception Handling – Making Your Code More Robust ⚠️
Introduction to modules and libraries 🏛️
🎯 Advanced Concepts (For the More Ambitious)
Object-Oriented Programming (OOP) – Classes, Objects, Inheritance 🏗️
Recursion and algorithm design 🧠
API and Web – Connecting Python to the web 🌐
Introduction to Databases – Storing and Retrieving Data 🗄️
🎨 Practical Projects & Applications
Creating simple games 🎮
Automation of repetitive tasks 🔄
Data analysis with pandas 📊
Web scraping and working with APIs 🌍
Introduction to Artificial Intelligence and Machine Learning 🤖 (optional for advanced learners)
🎯 An Interactive and Fun Learning Experience
Live Online Classes – Learn from home with interactive sessions via screen sharing.
Tailor-made lessons – Content adapts to your level for an effective and personalized learning journey.
Practical exercises and projects – Less theory, more practice! Learn with real-world examples.
Caring and motivating environment – No pressure, no judgment: progress at your own pace.
Practical application – Each concept learned is applied immediately through exercises and mini-projects.
🔔 For Who?
This program is ideal for:
✅ Complete beginners – If you’ve never written a line of code, no worries! The lessons start from scratch.
✅ Students – To prepare for programming courses, computer science exams or competitions.
✅ Self-taught – If you want to add Python to your skillset, this course offers you structured support.
✅ Professionals and people in retraining – Python is a sought-after skill in data science, automation and web development.
✅ Tech Enthusiasts – Curious to learn code? This course makes learning Python both fun and useful.

🚀 Ready to Embark on Your Python Adventure?
Join the "🐍 Personalized Private Lessons – 💻 Learn to Code and Program in Python!"
Gain the skills and confidence to write clean, efficient, and powerful code.

Sign up today and take your first steps into the exciting world of Python programming! 🔥
verified badge
I offer Microsoft Word, Microsoft Excel, Microsoft PowerPoint, Microsoft Office sessions

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Excel is a spreadsheet software from the Microsoft Office suite developed and distributed by the publisher Microsoft. It is used to create spreadsheets, tables, graphs, etc.

Powerpoint is a presentation software developed by Microsoft. It is part of the Microsoft Office suite. It is used to create presentations, slide shows...

I am waiting for your message.
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Applying concepts from Hilpisch's Python for Finance.
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Understanding algorithms is essential for anyone pursuing computer science or programming. In this course, I provide a structured approach to learning algorithms—from fundamental concepts like sorting and searching to advanced techniques such as dynamic programming and graph theory. Whether you're preparing for exams, coding interviews, or aiming to improve your problem-solving skills, this course is designed to build strong algorithmic thinking. Through practical examples and step-by-step explanations, I help students master the logic and techniques needed to write efficient and elegant code.
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I teach coding to beginners and intermediate students.
Lessons focus on logic, basic programming, and practical exercises.
Classes are adapted to the student’s pace.
Students can choose between website or mobile app development.Hands on dev
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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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You have a kid that's interested in programming?? Set up a class for him with me. Aya a software engineer turned teacher. I was a software engineer for 3 years before I joined the teaching industry and I currently teach computer science in Chichester College in United Kingdom. I want to advocate for computer science and help familiarise kids at a young age with programming in Python.

Send me a message let's chat about what you want your kid to learn and what I can offer! :)
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Learn Python by building something you’ll actually use

Ever wanted to code but had no idea where to begin? You’re in the right place. In these relaxed, one-on-one lessons, you’ll go from zero to writing real programs, with no experience required.

Together, we’ll choose a project that fits your interests. Maybe it’s a video game you want to build or a quiz to challenge your friends, a chart built from your own spreadsheet, or a script that takes over a boring, repetitive task. Along the way, you’ll pick up the essentials (variables, loops, functions) and learn to read error messages without panic, so you can change your code with confidence.

Where you can go next

AI-assisted coding: Use tools like ChatGPT to brainstorm, decode errors, and improve your code, while learning to test its suggestions and explain how the final result works.
Machine learning: Train a simple model on a real dataset and see how well it predicts.
Your own project: Bring an idea from school, work, or a hobby, and we’ll break it into steps you can build at your own pace.

Your instructor

I’m an engineer with a master’s degree from Nagoya University and research experience in applied AI and computer vision. I explain every concept in plain language, then give you time to try it yourself with live feedback, so you’re never stuck alone.

Ready to start?

Send me a quick message and let's do your first coding project together.
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Contact Matteo