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Since September 2026
Instructor since September 2026
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Programming & Web Development – Tutoring for HTL, FH, university studies and personal projects
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From 66 C$ /h
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Do you need support with programming, are you stuck on a task, or do you finally want to truly understand the basics of web development?

I support school students, students at technical colleges, universities of applied sciences, and universities, as well as beginners, in programming and modern web development. The lessons are tailored to your current knowledge level and the specific topic you need support with.

Together we can develop fundamental concepts, solve problems, study for exams, or work directly on your own project.

Possible topics include:

• JavaScript and TypeScript
• HTML and CSS
• Fundamentals of programming
• Variables, functions, objects and classes
• Interfaces, types and generics
• Asynchronous programming
• Working with APIs
• Angular and modern web applications
• Databases and PostgreSQL
• Git and version control
• Debugging and systematic troubleshooting
• Understand and improve code
• Preparation for tasks, projects and exams

What's particularly important to me is not simply providing a ready-made solution. Together, we'll look at where a problem arises, how to analyze it step by step, and how you can arrive at a solution yourself.

If you already have a specific task or project, you can bring it directly to class. We can go through existing code together, find errors, and clarify any open questions.

The lessons are suitable for beginners as well as students who already program and need support with specific topics. I will tailor the content and pace to your individual prior knowledge and goals.
Location
location type icon
Online from Austria
About Me
I am a freelance software developer and have been working professionally in modern web development for many years. My focus is on Angular, TypeScript, and the development of large web applications.

I've been working with Angular since 2016. Today, I run my own software agency, WeekndDevs, developing both custom software solutions for clients and our own software products. This means I'm familiar not only with the theory behind individual technologies but also with the challenges that arise in real-world projects – from architecture and code quality to debugging and performance, as well as testing, deployment, and long-term maintainability.

When teaching, it's important to me to explain technical topics in a clear and practical way. I don't want to simply provide a ready-made solution, but rather show why something works and how to arrive at a good solution independently.

I tailor the lessons to each student's individual level of knowledge. Beginners can start with the basics, while with advanced students or developers we can work directly on specific problems, existing code, or architectural questions.

It is particularly important to me that questions can be asked at any time and that any uncertainties are truly clarified. The goal is not to cover as much material as possible in a short time, but rather to understand the connections and then be able to apply what has been learned independently.

My areas of expertise include:

• Angular and TypeScript
• JavaScript, HTML and CSS
• modern front-end architecture
• APIs and full-stack web development
• NestJS and PostgreSQL
• Git, testing and debugging
• Performance and code quality
• professional development tools and workflows

The course is suitable for school pupils, HTL/FH/university students, career changers as well as developers already working in the field.

If you are working on your own project or are stuck on a specific task, we can gladly work directly with your existing code and develop a solution together.
Education
Alpe-Adria University in Klagenfurt, Applied Computer Science from 2012 to 2016.
IT-HAK diploma with a focus on information technology and business.

Since then, continuous professional development in modern web development, especially in Angular, TypeScript, JavaScript, software architecture, testing and full-stack development.
Experience / Qualifications
Since 2017 I have been self-employed in software development and have been working intensively with Angular since 2016.

Over the course of my professional career, I have worked on various web applications and larger software projects, gaining particular experience in Angular, TypeScript, frontend architecture, APIs, databases, testing and performance optimization.

Besides development, my responsibilities also included training and supporting other developers. I guided developers on their introduction to Angular and developed training materials for Angular.

Today I run my own software agency, WeekndDevs, and develop individual software solutions as well as my own products such as Turniermeister, Bierblock and else.events.

This allows me to not only impart theoretical knowledge in class, but also to explain many topics based on real experiences from professional software projects.
Age
Children (7-12 years old)
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
German
English
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
Do you want to develop modern web applications with Angular and TypeScript, need support with an existing project, or want to deepen your knowledge in a targeted way?

In my classes, you'll learn Angular and TypeScript through hands-on experience, using concrete examples and real-world applications. It's not about memorizing commands or copying pre-existing code. My goal is for you to understand how Angular works, why certain solutions are beneficial, and how you can independently solve technical problems later on.

The lessons are individually tailored to your current knowledge level and your goals. We can start with the basics or work specifically on advanced topics.

Possible topics include:

• Fundamentals of TypeScript, JavaScript, HTML and CSS
• Components and modern Angular project structures
• Signals and reactive data processing
• Inputs, outputs and communication between components
• Services and Dependency Injection
• Routing and lazy loading
• Forms and validation
• RxJS and asynchronous data
• REST APIs and the connection to backends
• Architecture of larger Angular applications
• Debugging, performance, and code quality
• Testing and modern development tools
• Git, ESLint and professional work on software projects

If you're already working on your own project, a school, technical college, university, or university assignment, or a professional application, we can also work directly with your existing code. Together, we can analyze errors, implement features, improve the architecture, or clarify any open questions.

I have been working professionally with Angular since 2016 and today, as a freelance software developer, I create both custom applications and my own software products. This allows me to share not only the fundamentals but also experience gained from real-world, long-term software projects.

The course is suitable for beginners, pupils and students as well as for junior and more experienced developers who want to better understand and use Angular and TypeScript more professionally.
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Do you want to learn how to create a complete modern web application – from the frontend to the backend and the database?

In this course, we develop full-stack applications using Angular, TypeScript, NestJS, and PostgreSQL. We don't just look at individual technologies in isolation, but primarily at their interaction within a real-world application.

The lessons are practice-oriented and adapted to your current level of knowledge. We can develop an application together from scratch or work directly on your existing project.

Possible topics include:

• Angular and TypeScript in the frontend
• NestJS and TypeScript in the backend
• Structure and organization of REST APIs
• Communication between frontend and backend
• PostgreSQL and data modeling
• Authentication and user management
• Validation and error handling
• Services and Dependency Injection
• clean project and software architecture
• Git and professional development workflows
• Debugging and testing
• Deployment and operation of a web application

My goal isn't simply to provide you with finished code. You should understand how the individual parts of an application interact, why certain architectural decisions are made, and how you can later develop full-stack applications independently.

If you are already working on your own application, a school, technical college, university of applied sciences or university project, we can work directly with your existing code and solve specific problems together.

The course is suitable for developers who have mainly worked in the frontend so far and want to learn backend development, as well as for beginners and students who want to understand modern full-stack web development from the ground up.
Read more
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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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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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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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Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
This course is built around real problems and real code. We skip the textbook formulas and go straight to applying statistics and data science the way professionals do: with Python (pandas, NumPy, scikit-learn, matplotlib) and R (RStudio).
What we cover, adapted to your level and goals:
- Descriptive and inferential statistics (the ones that actually matter)
- Data cleaning, exploration, and visualization
- Regression, classification, and intro to machine learning
- Time series and forecasting basics
- R for statistical analysis and academic research

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

I use Python and R professionally as a working engineer — everything I teach comes from real application, not just academic exercises.
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While adults are still debating whether kids should use AI, they are already using it.
The question isn't "should they?" it's "how do we do it intelligently?"

In this course, your child will discover:
✓ What AI actually is: not magic, not mystery. How machines think, what they can do, what they can't
✓ How ChatGPT really works: not just "ask a question and get an answer," but why it responds that way, where it fails, when to trust it
✓ What LLMs are (Large Language Models): in language they understand, not tech jargon
✓ Create with AI: custom avatars, interactive stories, real projects using real tools
✓ Think critically about AI: Bias, privacy, creativity. What does AI do better than humans? What can't it do?
✓ Real-world applications: How AI transforms medicine, education, art, gaming, everyday life

Why this is different:
Most AI courses for kids teach "here's the tool, use it." I teach how to think about AI.
Your child will learn to see AI not as black magic or a solution to everything, but as a powerful tool with real limits.
And, more importantly: that they can control how they use it.

What they take home:
Real projects they created (custom avatar, interactive app, analysis of a real AI case study). A genuine understanding of how it works. And the ability to use AI responsibly and creatively.

Format: Online | 60–90 min sessions | Flexible, adapted to their age and pace

For curious kids asking "How does ChatGPT actually know things?"
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Python is a powerful and versatile programming language with countless possibilities. You can use it for data analysis, image processing, automation, software development, hardware control, and much more.

Do you want to create your own software?
Work with data or images?
Automate repetitive tasks?
Control or manage your own hardware?

Whether you are just starting to learn Python or already have a specific project and need some guidance, I would be happy to help you.

My goal is to explain things clearly, adapt to your level, and help you understand not only how to make something work, but also why it works.

Let's turn your ideas into working Python projects!
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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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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! 🔥
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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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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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# **Master C/C++: Build the Foundation of Modern Software Development**

Unlock the power of one of the most influential programming languages in computing history! Whether you're an absolute beginner or looking to deepen your expertise, this comprehensive C/C++ course delivers structured learning from fundamentals to advanced concepts that power operating systems, game engines, and high-performance applications.

## **Why Choose This C/C++ Program?**

**Industry-Relevant Curriculum:** Learn expert guidance on the design of effective classes, functions, templates, and inheritance patterns that form the backbone of professional C++ development. Move beyond basic syntax to understand how to write clean, efficient, and maintainable code that stands the test of time.

**Templates & Generic Programming Mastery:** Go beyond introductory material with in-depth coverage of templates—the cornerstone of modern C++—enabling you to create robust, reusable code components that work across multiple data types. Discover how function templates, class templates, and variadic templates work to maximize your coding efficiency.

**Practical, Hands-On Approach:** This isn't just theory! You'll build real-world projects that demonstrate memory management, object-oriented programming, and system-level programming techniques used in today's technology landscape.

## **Your Learning Journey**

Our structured path takes you from writing your first "Hello World" program through advanced template metaprogramming, with special attention to modern C++ standards (up to C++20). You'll gain the confidence to tackle complex programming challenges and understand the "why" behind effective C++ practices—not just the "how."

## **Transform Your Career Today**

C/C++ skills remain in high demand across industries from finance to gaming to IoT. By mastering these foundational languages, you'll develop problem-solving abilities that translate to any programming environment.
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These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

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

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

🎯 Training Objectives

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

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

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

🛠️ Teaching method: Understand before writing

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

🚀 Learner's result

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

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

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

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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📊Microsoft Office: To establish your office skills, manage data via Excel, write professional reports with Word, and prepare impressive presentations with PowerPoint.

📐 AutoCAD: To learn engineering drawing and design two-dimensional and three-dimensional plans with high accuracy and speed.

🛣️ Civil 3D: To learn road design, network design, surveying, and quantity surveying in a scientific and practical way
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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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