Engineering, Robotics & Arduino for Beginners | Hands-on Programming and Electronics

From 17 € /h

If you are curious about robotics, Arduino, programming, or engineering and want to learn in a simple and practical way, this class is made for you.

Together, we will explore how electronic components work and learn step by step how to program Arduino boards using C++. Through fun hands-on projects, students will create systems using LEDs, sensors, motors, and other smart components used in real robotics projects.

My teaching style focuses on practice, creativity, and understanding rather than only theory. I aim to help students build confidence while learning how to solve problems and think like engineers.

I have participated in several robotics and STEM experiences, including FIRST Tech Challenge (FTC), World Robot Olympiad (WRO), and space-related programs and projects such as space camps and engineering activities focused on innovation and technology. These experiences helped me gain practical knowledge that I now share with students in an easy and engaging way.

I can also teach CATIA V5 for students interested in mechanical design, engineering projects, and 3D modeling. These lessons can help students better understand mechanical engineering concepts and learn how to design professional parts and assemblies used in real engineering projects.

This class is perfect for beginners and intermediate learners who want to start or improve their journey in robotics, technology, mechanical engineering, and space-related fields.

Extra information

Bring a laptop if possible for programming and simulations.

Having an Arduino kit is recommended, but it is not mandatory for beginner lessons. If you do not have electronic components or an Arduino board, we can still learn and build projects using professional simulation platforms that allow students to practice virtually.

Classes include practical demonstrations, simulations, and project-based learning to make the experience interactive and engaging.

For highly motivated students who want to go further, there may also be opportunities to work on real projects and collaborate with technology organizations, robotics initiatives, or STEM activities to gain real world experience.

Location

Online from Morocco

About Me

I am a student passionate about robotics, engineering, and space technologies. Over the past few years, I have been deeply involved in STEM through competitions, volunteering, and hands-on technical projects that helped me build both practical skills and teamwork experience.

I have worked as a Technical Lead in FIRST Tech Challenge (FTC) robotics teams for multiple seasons, where I was involved in designing, building, and programming robots while solving real engineering challenges with my team. I also took part in events such as the World Robot Olympiad (WRO) and volunteered in the FIRST LEGO League (FLL) national competition at UM6P Benguerir, as well as serving as a Field Tester in the FTC Morocco Championship.

One of my most meaningful experiences was being selected among 30 students from more than 1,650 applicants to attend AMAZE Space Camp. There, I worked on space-related projects and learned how engineering and collaboration are essential in real-world innovation.

Alongside robotics, I have developed strong skills in Arduino programming, electronics, embedded systems, automation, and CATIA V5 for mechanical design and 3D modeling. I enjoy turning ideas into real projects and helping others understand complex concepts in a simple and practical way.

Today, I focus on sharing what I have learned by teaching robotics, programming, and engineering in an accessible and hands-on approach, especially for beginners who want to start their journey in STEM.

Education

CPGE TSI (Classes Préparatoires aux Grandes Écoles – Technology and Industrial Sciences) Ben Mellal-Morocco
Focused on mechanical engineering, industrial systems, mathematics, physics, electronics, and advanced engineering concepts.

Experience / Qualifications

Over the past few years, I have been actively involved in robotics, engineering, and STEM activities through competitions, volunteering, and technical projects.

I worked as a Technical Lead in FIRST Tech Challenge (FTC) robotics teams for multiple seasons, where I helped design, program, and develop robotic systems while working closely with team members to solve technical challenges.

I also participated in robotics competitions and events such as the World Robot Olympiad (WRO), volunteered in the FIRST LEGO League (FLL) national competition at UM6P Benguerir, and worked as a volunteer and Field Tester during the FTC Morocco Championship.

Beyond robotics, I was selected among 30 students from more than 1,650 applicants to participate in AMAZE Space Camp, where I gained experience in space-related activities, teamwork, and engineering projects. I have also participated in STEM conferences, technology initiatives, and innovation programs.

In addition, I have practical experience with Arduino programming, electronics, embedded systems, automation, and CATIA V5 for mechanical design and 3D modeling. I enjoy sharing this experience with students and helping them better understand technology and engineering through practical and interactive learning.

Age

Children (7-12 years old)

Teenagers (13-17 years old)

Adults (18-64 years old)

Student level

Beginner

Intermediate

Duration

60 minutes

90 minutes

The class is taught in

English

Arabic

French

Skills

Robotics

Mechanical engineering

Computer programming

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

4.85

(13)

Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

Matías

4.85

(13)

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.

This popularity means that Python is constantly evolving. It offers a wide range of tools and libraries, which are free and very varied.

As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

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.

Beyond these general principles, there is no magic rule or method. Some approaches work with some students but not with others. Adaptation to individual needs is therefore the main objective of private lessons. So I will do my best to find what motivates and helps my student.

Haider

4.85

(13)

Welcome!

I have already completed my master’s degree in mechanical engineering and am currently doing my doctorate.

Tutoring is offered (online) in

✔ Math

✔ Physics

✔ Technical mechanics (statics, strength theory, kinematics)

✔Technical drawing

✔ Machine elements

✔ Thermodynamics

✔ Fluid dynamics

+ other subjects on request

When contacting please
Class / study / training and subject
notify!

I am looking forward to hearing from you.

Reza

4.85

(13)

I hold a PhD in Mechanical Engineering and currently, I am working as a post-doctoral researcher in the Aerospace Engineering Faculty at TU Delft (Delft University of Technology).

I have extensive experience in teaching various Mechanical design packages, including LS-DYNA, ANSYS, APDL programming, ABAQUS, MATLAB, SolidWorks, Cura, and Symbolic MATLAB.

Some of the finite element modeling and numerical simulations I have worked on include:
- Multiscale finite element modeling for fatigue crack propagation in porous materials.
- Analysis of multiple-layer sandwich structures' resistance to bird-strike impact [Read paper].
- Investigation of debonding propagation in aluminum and glass/epoxy composite joints under fatigue loading using Fracture Mechanics principles.
- Computational prediction of the fatigue behavior of additively manufactured porous metallic biomaterials.
- Study of the effect of material type, stacking sequence, and impact location on pedestrian head injury in collisions.

If you have any additional questions before starting the class, please don't hesitate to ask me. I am here to help! :)

Enrique

4.85

(13)

Don't settle for anything less than excellence.
I am an Aerospace Engineer with a Master's degree in Quantum Physics and have completed Ph.D. work at the University of Cambridge in Computational Physics. Additionally, I have 4 years of experience developing MATLAB and possess deep programming skills in MATLAB/Simulink family, C/C++, Fortran, and Python.

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

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

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

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

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

Gaëlle

4.85

(13)

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?"

Tim

4.85

(13)

Need help with mechanics, physics, or thermodynamics? As a 33-year-old civil engineer, I'm happy to help! I'll learn at your own pace, using plenty of examples to illustrate the material. I have years of experience teaching both simple and complex subjects.

The lessons run as follows. First, we look together for the student's biggest stumbling blocks. These can be related to the subject matter as well as to the study method. From there, I work at the pace of the student and encourage them to ask as many questions as possible. I also give tips and tricks, and improve their working methods where necessary. During the lesson I give many examples to make the subject matter more interesting and we solve exercises together. Once practiced from the lesson, I mastered challenging exercises to also test the deeper understanding of the subject matter. In this way I try to optimally prepare the student for his/her exam test.

However, learning should also be enjoyable. That is why I always strive for a bond with the student through a spontaneous and positive approach. I am also very patient. All this to solve and improve the problems.

Are you interested? Don't hesitate to receive me!
Please come!

Tim

Giuliano

4.85

(13)

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!

Salah

4.85

(13)

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.

Baia

4.85

(13)

I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work.

Topics include:
Python fundamentals through a finance lens (data structures, functions, control flow).
Working with financial data and datasets.
Performance benchmarking and writing efficient code.
Applying concepts from Hilpisch's Python for Finance.

Meriem

4.85

(13)

Python is today one of the most widely used programming languages in the world, both in Data Science, Artificial Intelligence, Web Development and for task automation.
In this course, I will guide you step by step according to your level:

Beginner: basics of the language (variables, loops, conditions, functions).

Intermediate: data manipulation (Pandas, NumPy), file management, object-oriented programming.

Advanced: practical projects (data analysis, machine learning, automation, API, web scraping).

My goal is to make learning clear, practical, and motivating. You'll not only learn how to code in Python, but also how to structure your projects and apply your knowledge to real-life scenarios.

Farouk

4.85

(13)

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

Alonso

4.85

(13)

I am a Mechanical Engineer, Master in Mechanical Engineering and Retired Full Professor from the University of Zulia (Venezuela).
I taught university-level engineering courses for over 30 years. I helped train more than 9,000 students. I supervised over 50 undergraduate theses. I taught undergraduate and graduate courses in various subjects related to mechanical engineering (Mathematics, Physics, Dynamics, Mechanisms, Strength of Materials, Stability, Solid Mechanics, Fluid Mechanics, Machine Elements, Machine Design, Statics, Mechanics of Machines, Mechanics of Materials, Rational Mechanics, Principles of Lubrication, Simulation of Sliding Bearings, Advanced Mechanics of Materials, Stress Analysis, Failure Theories, Structures, Mechanisms). In addition, I have given private lessons in Physics, Statics, Strength of Materials, Stability I, Stability II, Fluid Mechanics, Rational Mechanics, Mechanics of Materials, Dynamics, Elements of Machines and Mechanisms for 7 years to students from different countries of the world (online) and in particular to students from Argentina (online and in person) from various universities in the country (UBA, ITBA, UTN, UNLZ, UADE, etc).

Stop struggling with Strength of Materials! Many students get lost among so many formulas. My goal is for you to understand the physical logic behind each problem. I am a university professor and offer personalized tutoring for undergraduate and graduate students.
What we will do:
- Solve exercise guides.
- Intense preparation for midterms/finals.
- Theoretical explanations focused on practice.
I have extensive experience teaching courses related to Mechanical Engineering at both the undergraduate and graduate levels. I have taught courses such as Strength of Materials, Stability I, Stability II, Statics, Mechanics of Materials, Elasticity, Mechanics of Solids, Fluid Mechanics, Machine Elements, Rational Mechanics, Stress Analysis, Mechanisms, Mechanics of Machines, and Advanced Mechanics of Materials. Furthermore, I have a strong background in Mathematics, Mathematical Analysis, Calculus, and Physics (Statics, Kinematics, and Dynamics). I emphasize teaching through problem-solving and practical applications.
For online classes I use a digitizing tablet connected to the computer and an interactive digital whiteboard that allows me to develop and explain the solution to exercises or the theory in real time directly on PDF or JPG files (they can be exercise or theory guides), which makes the class more enjoyable and efficient and also guarantees the same quality as a face-to-face class.

I am a University Professor with extensive experience in teaching subjects related to Mechanical Engineering at the Undergraduate and Postgraduate levels. I have taught subjects such as Strength of Materials, Stability, Elasticity, Solid Mechanics, Machine Elements, Rational Mechanics, Stress Analysis, Mechanisms, Machine Dynamics and advanced materials mechanics. In addition, I have a solid background in Mathematics, Mathematical Analysis, Calculus and Physics (Kinematics and Dynamics). I emphasize through problem solving and practical applications.

Ammar

4.85

(13)

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.

Abdelmalek

4.85

(13)

This hands-on training pathway is designed to help students kickstart any project, specifically tailored for OT labs and industrial applications. Starting from absolute scratch, students will build a strong foundation in Python programming through practical, industry-relevant concepts.

Curriculum Outline: |
01 - Python Environment Setup & Basics |
02 - Python Variables, Numbers, Bytes & Hex |
03 - Control Flow Logic Functions |
04 - Data Structures (Lists, Tuples, Dictionaries & Sets) |
05 - String Formatting, Comprehensions & Exception Handling |
06 - File IO, Pathlib & Context Managers |
07 - Object-Oriented Programming (Classes & OOP) |
08 - Standard Library, Modules & Networking Basics |

Assessment & Evaluation:
Students will take a mini-test after the completion of each module. Additionally, an Audit & Performance Evaluation report will be sent following the tests.
Duration:
5 days to 15 days (depending on the pace of the cohort)