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React.js – Basics + Easy Mini Project for Beginners
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From 30.37 C$ /h
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This course is for beginners and apprentices who want to learn React.js and create their first mini web project.

You will learn :

Installing and configuring a React environment

Basic concepts: components, accessories, condition

Event and form management

Using Hooks (useState, useEffect)

Simple connection to an API or local storage

Completion of a mini practical project (e.g., To-Do List, Portfolio, Mini Dashboard)
Extra information
Laptop required

Install Node.js and VS Code before the course

No prerequisites for beginners, just motivation!
Location
location type icon
Online from Morocco
About Me
I am a full stack web and mobile developer and hold a Master’s degree in ISI (Information Systems Engineering). I have extensive experience in designing, developing, and deploying web and mobile applications, and I teach students how to build real-world projects from scratch.

Skills and Competencies:

Front-End Development:

HTML5, CSS3, JavaScript, TypeScript

Responsive Web Design, Bootstrap, Tailwind CSS

Frameworks: Angular, React.js, Vue.js

UI/UX design principles, interactive web interfaces, single-page applications (SPA)

Back-End Development:

PHP programming, Symfony framework

Node.js & Express.js

RESTful API development and integration

Database management: MySQL, PostgreSQL, Firebase

Mobile Development:

Flutter (front-end), Dart programming

Mobile apps connected to APIs and databases

Firebase integration (authentication, storage, real-time data)

Additional Skills:

Git/GitHub for version control

Deployment: Heroku, Firebase Hosting, cPanel

Debugging, optimization, and error correction

Project architecture (MVC, modular code)

Agile methodology and project management basics

What I offer:
I guide students step by step, provide personalized advice, mentorship, and code review. I help apprentices and beginners complete their web or mobile projects successfully.
Education
Master’s Degree in ISI (Information Systems Engineering), Faculty of Sciences, Qadi Ayyad

Professional Bachelor’s Degree in Web Technology and Programming, Faculty of Sciences, Qadi Ayyad

DEUG in Mathematical and Computer Sciences, Faculty of Sciences, Qadi Ayyad
Experience / Qualifications
Full Stack Mobile Develope

Full Stack Web Developer

Experience in building real-world applications for apprentices, students, and beginners

Mentoring and supporting students in projects, debugging, and best practices
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Duration
60 minutes
The class is taught in
French
English
Arabic
Reviews
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
This programming course is intended for beginners as well as people who already have a foundation and wish to improve their skills.
We will cover programming logic, the basics of algorithms and practice through concrete examples.

Depending on your level and objectives, the course may include:

Introduction to programming

HTML, CSS, JavaScript

PHP / Node.js

Databases (MySQL, PostgreSQL)

Understanding and correcting errors in the code

Completion of small practical projects

The approach is progressive, clear, and practice-oriented.
Read more
Personalized support for students, freelancers and entrepreneurs wishing to succeed in their IT projects.

Help with:

Project structuring

Technology choices

Specifications

Code correction and improvement

University projects (final year projects, final year projects, dissertations)

Finalization and delivery of the project
Read more
Show more
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Data science, statistics & mathematics – clearly explained, personally supported.
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✅ Cybersecurity: Ethical hacking, data protection, network security
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🔹 Cambridge A-Levels & O-Levels Computer Science – Preparing students for advanced computing concepts, problem-solving, and algorithm development.
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📌 Mentored students to achieve top grades in Cambridge ICT & Computer Science exams.
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📌 Conducted coding boot camps and cybersecurity workshops to enhance practical learning.
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With a strong commitment to student-centered learning and technological innovation, I am dedicated to shaping future tech leaders and empowering learners with skills relevant to careers in technology, data science, and software development.
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This course provides a foundational understanding of Information Technology, data centers, covering architecture, power & cooling, networking, storage, virtualization, security and lots more. Learn best practices for efficiency, scalability, and reliability while exploring emerging data center solutions. Ideal for IT professionals, engineers, and facility managers involved in data center deployment or management.

This course offers a comprehensive exploration of Information Technology, data center infrastructure, guiding students through the entire lifecycle—from initial design and planning to day-to-day operations and long-term performance optimization. Students will learn the critical components of data center design, including site selection, power and cooling systems, space planning, networking, and physical security. The course also covers operational best practices, monitoring tools, energy efficiency strategies, disaster recovery planning, and emerging trends. By integrating technical, environmental, and management perspectives, students will gain the knowledge and skills required to build and maintain high-performance, cost-effective, and sustainable data center environments.
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This course introduces students to the fundamentals of Information and Communication Technology (ICT) and its role in modern society. Topics include computer hardware and software, digital communication tools, internet technologies, data management, cybersecurity, and emerging trends. Students will gain practical skills in using productivity software, conducting online research, and understanding the ethical and responsible use of digital resources. The course emphasizes both technical proficiency and digital literacy, preparing learners to confidently navigate and contribute to a technology-driven world.
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Data science, statistics & mathematics – clearly explained, personally supported.
My name is Kian, an experienced tutor from Bern. I support students, career starters, and professionals on their journey into the data-driven world—whether in their studies, projects, or everyday work.

With my structured, understandable, and motivating approach, I'll help you not only solve problems but also understand data, recognize connections, and make informed decisions. My lessons are personalized, efficient, and at eye level.

Who I am – and why I teach:
I teach in Bern and successfully completed the MAS program in Statistical Data Science at the University of Bern, focusing on statistics, mathematics, and data science. For several years, I have been passionately teaching, both in academic contexts and for professionals who want to think and work more data-driven.

In parallel to my teaching, I have implemented numerous data science projects – from exploratory analysis and data modeling to decision support in a business context. This combination of theory and practice makes my teaching particularly close to reality while remaining accessible.

I love making complex topics tangible, creating aha moments, and empowering people to handle data confidently. For me, tutoring isn't just about imparting knowledge—it's about developing their minds on equal terms.

-What you can expect from me:
One-to-one lessons with a focus on data comprehension, statistics & analytical thinking
Support with projects, assignments, exams or getting started in the data world
Practical explanations – step by step and adapted to your everyday life
Teaching modern methods for data analysis, modeling & interpretation
Long-term strategies for problem-solving & structured thinking
Flexible lessons in Bern or online – personal, competent & reliable

Why I can help you understand data science:
Because I work at the interface between science and practice. I know how quickly you can get lost in formulas and tools—and I'll help you see the common thread:
How data tells stories, how you analyze it, and how you make smart decisions.

With me, you won't just learn methods—you'll learn how to think with data. Whether in your studies or in your career, I'll guide you in truly understanding data and applying it confidently.
Learn data analysis.
Analyze and model complex data sets – understandable, practical and with structure.
If you're ready to get to grips with data, I'm ready to guide you.
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Objective: To understand AI without fear, to use it to simplify one's life, to know how to identify digital traps, and to use Word, Excel, etc. without difficulty.

1: Demystifying AI (What exactly is it?)
AI is not a movie robot: Difference between fiction and reality.

How it works (simply): The image of the "giant library": AI has read billions of books and uses them to predict the continuation of a sentence or create an image.

Where is it already present? Spell checkers, Netflix/YouTube suggestions, GPS, and voice assistants (Siri/Alexa).

2: Using AI to make life easier
Conversing with AI (ChatGPT, Claude, Gemini):

Ask him to write an administrative email or a complex letter.

Summarize a long newspaper article or document.

Plan a travel itinerary or find recipe ideas with what's left in the fridge.

AI for creativity and memory:

Generate images to illustrate a birthday card (Midjourney, DALL-E).

Using AI to restore or colorize old family photos.

3: Learning to "talk" to AI (The Art of the Prompt)
The context method: Why "Give me a cake recipe" is less effective than "I am allergic to gluten and I am hosting 4 people, give me a simple chocolate cake recipe".

The expert's role: Learning to tell AI "Act like a travel guide" or "Act like an expert gardener".

4: Precautions and Critical Thinking (The Survival Guide)
"Hallucinations": Understand that AI can make false claims with complete certainty (never take medical or legal advice from AI without verification).

Privacy protection:

Never give sensitive data (social security number, passwords, bank details) to an AI.

Knowing that everything we write to the AI is potentially used to train it.

Spotting "Deepfakes":

How to recognize a doctored image or video (details on the hands, strange reflections, slightly metallic voice).

Verify the information: the golden rule of cross-referencing sources.

5: Ethics and Impacts (To go further)
Copyright: Who owns an image created by AI?

The environmental impact: The water and energy consumption of AI servers.

The future: Will AI replace us or assist us?
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This class is perfect for students who are new to programming and want to learn how to code in Java and Python. We will start from the basics and slowly build up confidence by learning how programs work, how to write simple code, and how to solve problems step by step. Lessons include easy examples, practice exercises, and clear explanations. No previous coding experience is needed—just curiosity and willingness to learn.
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