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Trusted teacher
This teacher has a fast response time and rate, demonstrating a high quality of service to their students.
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Since June 2020
Instructor since June 2020
Translated by GoogleSee original
Programming Languages / Databases / Frameworks / Devops
course price icon
From 71.83 $ /h
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PROGRAMMING

C language
C ++ language
HTML language
CSS language
JavaScript language> NodeJs> JQuery> Ajax> Json
XML language: XPath, Xslt, Xlink, Fop, Sax, Dom,
Language Java, Struts, Spring, JSF, JEE, EJB
Scala language
Language PHP, ZendFramework, CodeIgniter, Symphony, Mantis, Testmaker,
Language COBOL 1 COBOL 2 COBOL Object MicroFocus Fujitsu PacBase
FORTRAN language
LISP language, PROLOG
UML language
SQL language

MODELIZATION

Object Design Patterns,
Python language, Web Scraping, Scrapy, Selenium, BeautifulSoup
BigData Hadoop, Spark, Hive, Oozie, Zookeeper, Pig, Flume,
Neo4J, Redis
Elasticsearch, Kibana, Logstash
DataScience R language

DATABASES or INFORMATION SYSTEM

Database Oracle, Mysql, Sybase, Ingres, Universe, Informix, Access

FRAMEWORKS

BPM: jBPM, Camunda
ETL: Talend, Datastage
ERP: Odoo
CMS: Drupal
CRM: SugarCRM
E-Commerce: Prestashop, Magento
BI Lumira Business Objects

DEVOPS

Sonar code review,
Maven, Gradle, Continuous Integration Jenkins, Archiva, Confluence, Jira
JUnit test
Extra information
Good internet connection> 2 MB
Location
location type icon
Online from France
About Me
Pedagogy approved for more than 30 years in the training of students, employees, job seekers, change assistance, upgrading in the largest French training companies: Bull Formation, Demos, Atos, Cegos, ...
Education
Doctorate in Deductive Databases at the University of Paris-Sud Computer Science Research Laboratory Bat 490 Orsay
Master's degree in computer science applied to management at the Institut Supérieur de Gestion
Experience / Qualifications
Doctorate in Deductive Databases at the University of Paris-Sud Computer Science Research Laboratory Bat 490 Orsay
Master's degree in computer science applied to management at the Institut Supérieur de Gestion
Age
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
French
English
Availability of a typical week
(GMT -04:00)
New York
at teacher icon
Online via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
Are you going to continue your studies in France?
In the first year of computer science, we try to ensure that students master:
the techniques,
the tools,
basic methods: design methods, algorithms, languages, operating systems, components of computing machines, etc.
Read more
The second year is oriented towards design and integration activities; the training allows students to confront more complex problems: information systems, real time, networks, distributed architectures, artificial intelligence, compilation, production management ...

The emphasis is on coordination within the group: work sometimes stops after the detailed design.
Read more
Show more
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As a Geophysics PhD student, I rely heavily on programming tools like Matlab, Python, and R for data analysis, mathematical modeling, plot results and much more.

After a lot of requests from students I created this course which is specifically meant to give you support completing your final programming projects.

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Sandrine.
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For many years, I have successfully supported Swiss students in the fields of statistics, data analytics, machine learning, and artificial intelligence. I have gained extensive experience using R as a statistical programming tool and know exactly what students in Switzerland are required to do. I have numerous sample projects, datasets, and exam questions at my disposal and have prepared many students for their assignments and exams in a targeted, sustainable, and highly successful manner. My focus is on explaining complex statistical procedures, algorithms, and data analyses in an understandable way, demonstrating them in a practical way, and building confidence in the secure handling of data. My goal is not only to improve grades, but also, in the long term, to develop a deep understanding of data-driven questions and modern technologies such as machine learning and AI, which are crucial in later professional life.

► How do I teach?

►I attach great importance to ensuring that my students truly understand statistical concepts, data analytics methods, machine learning, and AI models, rather than just applying them mechanically – this is how we achieve sustainable success in statistics, data analytics, and modern technologies.

►My success is based on my ability to flexibly adapt my teaching style to the individual needs of students in statistics, data analytics, machine learning and AI, including topics such as regression methods, logistic regression and other machine learning algorithms.

►I use practical, lively examples from statistics, data science and AI to clearly explain abstract concepts such as hypothesis testing, analysis of variance, linear and nonlinear models and to anchor them deeply in the memory.

►With patience and clarity, I break down complex statistical analyses, machine learning models, and data processes into their essential components so that no student is overwhelmed and can build a solid foundation in statistics, data analytics, and AI.

►I am convinced that trusting collaboration is crucial to reducing uncertainty in statistics or data science and creating a productive learning atmosphere.

►I offer intensive exam preparation and project support in statistics, data analytics, machine learning and AI, develop strategies to combat exam anxiety with my students and train them on real data sets and complex algorithms.

►As an experienced online tutor for statistics, data analytics, machine learning, and AI, I use modern tools such as interactive whiteboards and live coding sessions in R to make teaching as efficient and practice-oriented as possible.

►Locations: I teach statistics, data analytics, machine learning, and AI at your home, online, or by appointment – flexible, professional, and tailored precisely to your needs.
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This course is designed to introduce students aged 7 to 16 to the world of programming through two of the most widely used and industry-relevant languages: C++ and Python.

The class provides a structured, age-appropriate pathway into programming, whether the student is a complete beginner or already exploring coding through platforms like Scratch or Code.org. Emphasis is placed on understanding logic, building problem-solving skills, and writing real code in a supportive, project-based environment.

Taught by an engineering student with hands-on experience in both C++ and Python, this course empowers students to explore the power of code and build a strong foundation in computational thinking — essential for future studies in engineering, robotics, AI, or game development.
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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.
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After an initial assessment, this course is designed to transform your child from a passive consumer of technology into an active, ethical AI creator.

Based on the personalized roadmap developed in the first session, the 5-week program delivers structured, project-based learning tailored to your child's cognitive strengths and interests, specifically addressing any learning barriers identified during the diagnostic phase.

What we achieve in 5 weeks:

Week 1-2: Foundations of Machine Learning & Critical Thinking: We move beyond definitions, using interactive projects to understand how AI learns (data, bias, pattern recognition). This builds critical thinking about the technology they use daily.

Week 3-4: Ethical Generative AI for Creativity: Students learn to master prompt engineering to create digital art, stories, or game concepts using generative AI tools. Safety and Ethics are paramount: we focus on responsible usage, digital citizenship, and copyright basics.

Week 5: The Final AI Creator Project: personalized mini-project (e.g., training a simple image classifier or writing a fully co-authored AI story) to demonstrate autonomy and mastery of the core concepts.

As your specialized 10+ year tech educator and coach, I ensure:

SEN Integration: Continuous adaptation of project requirements and delivery methods to ensure students with Special Educational Needs (SEN) maintain confidence and measurable progress.

Skill Transfer: We teach skills that translate directly to school projects, not just AI theory, but advanced digital literacy and structured problem-solving.
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This online programming class is designed for students who want to build real technical skills in computer science and web development — not just learn theory, but actually create and understand how systems work.

I teach:

• Python programming (fundamentals, logic building, problem-solving, data handling)
• JavaScript (core concepts, DOM manipulation, interactivity)
• CSS (styling, layout systems, responsive design)
• Website Development (front-end foundations and structure)
• WordPress Development (customization, site building, content management)
• UI/UX Fundamentals (design thinking, layout clarity, user experience principles)

Students learn how to think computationally, break down problems logically, and build structured solutions. Lessons are practical and project-based, meaning students don’t just watch — they build.

For beginners, we focus on strong foundations: understanding how code works, writing clean syntax, and developing confidence in debugging.
For intermediate learners, we move into structured projects such as creating simple websites, improving layout design, adding interactivity, and understanding how front-end components connect.

My approach emphasizes clarity, structure, and application. I help students understand not only what to type, but why it works — which is the difference between copying code and truly understanding it.

This class is suitable for:
• School students exploring computer science
• Beginners transitioning into tech
• Learners preparing for academic computer science courses
• Individuals interested in web development skills

All sessions are fully online, interactive, and tailored to the student’s pace and goals.
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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
Good-fit Instructor Guarantee
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