Block programming and 2D video game creation: Scratch

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From 14 Fr /h

Scratch (6-14 years)
Learn to program with Scratch! Children will discover the fundamentals of programming by creating their own stories, games and animations. Through a visual interface, pictograms and code blocks, they will develop skills in logic, problem solving and creativity. The course is fun and easy to follow, perfect for young programmers who want to make their first 2D games.

All courses are personalized according to the needs of each child. It begins by teaching digital literacy and teaches both safe and online security practices and the use of free artificial intelligence tools.

Extra information

Equipment requirements:
Computer (NOT tablet, NOT smartphone)
Operating system: Windows 10, 11 or Mac version equal to or greater than 10.15 “Catalina” 64-bit. Minimum i5 or equivalent
8GB of RAM memory. Recommended fast hard drive (SSD)
32GB free storage space
Stable Internet connection. Recommended 15MB/s
Mouse (external mouse)
webcam
Headphones and microphone

Location

Online from Argentina

About Me

I am an educator passionate about technology and education with experience teaching programming and game design for children and teenagers.

I stand out for my patience, creativity and ability to explain complex concepts in a simple and understandable way. My goal is to inspire my students to explore the world of programming, 3D modeling, and graphic design applied to video games to help them develop skills that will be valuable in their academic and professional future.

Education

National Public English Translator at National University of Cordoba, Application development at CoderHouse, Frontend development at ADA. Baccalaureate completed at Nuestra Señora del Carmen Parish Institute.

Experience / Qualifications

Educator at: Steam School In A Box, Lifecole, Icyra Robotica, Steam Future Academy
Project management and sales strategies: Aysen Espacio, Beer Joint
R&D project management: Steam School In A Box, Lifecole

Age

Preschool children (4-6 years old)

Children (7-12 years old)

Teenagers (13-17 years old)

Adults (18-64 years old)

Student level

Beginner

Intermediate

Advanced

Duration

45 minutes

60 minutes

90 minutes

The class is taught in

Spanish

English

Skills

Computer programming

Game development

Video games

Availability of a typical week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Programming and creating 3D video games: Roblox

14 Fr /h

Roblox (6-14 years)
Create your own video game! Kids will learn how to design and program games using Roblox Studio. With basic concepts of Lua programming and 3D modeling, they will develop their creativity and critical thinking while having fun using Roblox Studio and Roblox Play. We will also use different types of plugins and scripts.

All courses are personalized according to the needs of each child. It begins by teaching digital literacy and teaches both safe and online security practices and the use of free artificial intelligence tools.

Programming and creating 3D video games: Minecraft

14 Fr /h

Minecraft (6-16 years)
Minigames in Minecraft! Children will learn to design and modify worlds in Minecraft (Bedrock and JAVA). They will develop skills in basic programming and creative 3D modeling while working on fun, collaborative projects using external applications such as: WorldPainter, AmuletMc, Mcreator, MakeCode, Tynker, NovaSkin, Tinkercad, Blockbench, SpriteCraft, Bridge v2 and much more!

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Most kids think coding is for "smart kids" or "future programmers."
It's not. Coding is how real people solve real problems.
In this class, we skip the theory. Your child creates real things.

What they'll do:
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✓ Program virtual robots: solve real-world challenges (navigate a maze, automate a task, build a system)
✓ Create in Minecraft Education: design worlds, automate constructions, solve logic problems
✓ Experiment with different languages: not just learn "the right way," but understand that there are many ways to think about a problem
✓ Collaborate and share: work with other kids, get feedback, improve their work
✓ Develop logical thinking: not just for coding, but for anything: solving math problems, science challenges, real-world situations

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We don't teach syntax. We teach how programmers think.
Most children's coding courses say "here's the code, copy it." We teach "what problem are we trying to solve? How could we break it into steps? What options do we have?"
When your child learns to think like a programmer, they can learn any language afterward.

What they take home:
A portfolio of 3–4 completed, working projects. The ability to say "I built this." And the deep understanding that code is a tool to make real things happen.

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What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
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- MATLAB and R available for engineering/science students

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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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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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Are you looking for personalized support to succeed in mathematics, physics or computer science? Whether you are a middle school, high school, university student or simply curious to learn, this multidisciplinary program is for you!

💡 Why Choose this Program?
This course offers comprehensive, tailored support to help you:

Strengthen your foundations and fill in your gaps.
Understand theoretical concepts in depth.
Master problem-solving methods.
Develop your computer skills, from introductory to advanced programming.
Prepare effectively for your exams and competitions.
With a human, motivating and caring approach, you will learn at your own pace in a calm and encouraging environment, without pressure or judgment.

📘 Mathematics – For All Levels
Mathematics may seem complex and abstract, but with the right method and clear explanations, it becomes logical and accessible.
This module covers:

Middle school level: Arithmetic, fractions, proportions, basic geometry, statistics.
High school level: Algebra, functions, equations, analytical geometry, probabilities.
Preparation for exams: Brevet, Bac, entrance exams for grandes écoles.
Advanced Mathematics: Differential and integral calculus, matrices, sequences and series for university level.
🔬 Physics – From Understanding to Application
Physics allows us to understand the world around us, from the laws of motion to electromagnetic phenomena.
This module will guide you through:

Middle and high school level: Mechanics, electricity, optics, thermodynamics.
University Level: Analytical mechanics, advanced electromagnetism, quantum physics, statistical thermodynamics.
Scientific Methodology: Knowing how to analyze a problem, formulate a hypothesis, apply physical laws and interpret the results.
Practical Applications: Virtual experiences, interactive simulations to better understand theoretical concepts.
💻 Computer Science – From Basics to Advanced Skills
In an increasingly digital world, mastering IT is essential. This module adapts to your level and your objectives:

Introduction to Computers: Understand how a computer works, use office software (Word, Excel, PowerPoint).
Programming Beginner: Learn to code in Python, JavaScript or C/C++ with clear explanations and practical exercises.
Advanced Programming: Optimized algorithms, complex data structures, object-oriented programming.
Project Development: Creation of web applications, automated scripts, simple video games.
Preparation for NSI Exams: Complete support to pass the Digital and Computer Science tests.
🎯 Interactive and Motivating Teaching
Dynamic Online Course: Learn from home with an interactive format using audio and screen sharing.
Method Adapted to Your Pace: Each course is designed according to your level and your objectives.
Practical Exercises and Concrete Projects: To apply theoretical concepts and learn while having fun.
Personalized Monitoring: Regular support to monitor your progress and adapt the program to your needs.
Encouragement and Motivation: A positive approach to building your confidence in your abilities.
🔔 For Who?
This program is aimed at:

Middle school and high school students wishing to strengthen their foundations or aim for excellence.
University students in science or computer science looking to deepen their knowledge.
Candidates for exams and competitions preparing for the Brevet, the Bac, or entrance exams to the grandes écoles.
Passionate self-taught people who want to learn to program or better understand the scientific world.
Adults in professional retraining wishing to acquire IT skills.
🚀 Ready to Succeed?
Join the "🎓 Multidisciplinary Program – 📘 Mathematics, 🔬 Physics & 💻 Computer Science for All Levels!" and benefit from personalized support to achieve your goals. Whether you want to improve your grades, pass your exams or develop programming skills, this program will give you knowledge, confidence and motivation.

Register today and take the first step towards success!

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Classes are adapted to the student’s pace.
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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

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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
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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.

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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.

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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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