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Since December 2024
Instructor since December 2024
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Web Development - API Programming with Java Spring Boot
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From 18 € /h
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This in-depth course will help you master the development of modern RESTful APIs using the Spring Boot framework. You'll learn how to build robust, scalable, and secure web applications using industry best practices.

Educational goals :
- Understand the fundamental concepts of REST APIs
- Master the architecture and components of Spring Boot
- Develop secure and efficient APIs
- Implement good development practices

Detailed program:

1. Introduction to Spring Boot
- Presentation of the framework and its ecosystem
- Configuration and setup of the development environment
- Structure of a Spring Boot project

2. REST API Fundamentals
- REST architectural principles
- HTTP methods and status codes
- Design of RESTful APIs

3. Development with Spring Boot
- Controllers and routing
- Management of HTTP requests and responses
- Data validation
- Exception management

4. Data Persistence
- Integration with Spring Data JPA
- Database configuration
- Creation of repositories
- Management of relationships between entities

5. API Security
- Authentication and authorization
- Implementation of JWT
- Role and permission management
- Protection against common attacks

6. Testing and documentation
- Unit and integration tests
- Automatic documentation with Swagger/OpenAPI
- Good testing practices

7. Deployment and monitoring
- Configuration of environments
- Deployment on different platforms
- Monitoring and logging
- Performance and optimization

Methodology :
- Theoretical courses with practical demonstrations
- Practical exercises and concrete projects
- Development of a complete application
- Code review and debugging sessions

Prerequisite:
- Knowledge of Java (OOP, collections, exceptions)
- Basics in web development and HTTP
- SQL concepts

Recommended duration: 15 hours (minimum)

By the end of this course, you will be able to:
- Design and develop professional REST APIs
- Effectively use Spring Boot and its ecosystem
- Implement advanced security features
- Deploy and maintain Spring Boot applications
- Follow development best practices

This training combines theory and practice to allow you to acquire concrete expertise in developing APIs with Spring Boot, a skill that is highly sought after on the job market.
Location
location type icon
Online from France
About Me
Doctor of ICT, senior technical advisor at the Orange group and co-founder of the service provider IM.Coding, I combine academic expertise and field experience to train the next generation of developers. With more than 10 years of experience in software development, I share my know-how acquired on large-scale projects, particularly in the fields of Java, Angular, DevOps and Cloud. My dual role as practitioner and teacher allows me to offer training rooted in real-life situations, enriched by the latest technological innovations. I am particularly focused on transmitting not only technical fundamentals, but also essential best practices and methodologies in the industry. My courses are based on real-life cases drawn from my professional experience and entrepreneurial projects, ensuring training that is directly applicable in a professional context. Join my sessions to benefit from pragmatic learning, focused on the skills sought by digital companies.
Education
Holder of a PhD in Information and Communication Technologies (ICT) obtained in 2019 from the Higher School of Communications of Tunis (SUPCOM), I have developed in-depth expertise in research and technological innovation. This doctoral course follows my telecommunications engineering degree, obtained in 2014 also at SUPCOM, where I acquired solid technical and theoretical foundations. This dual training of excellence allowed me to develop a unique approach, combining academic rigor and innovative vision, which I apply today in my training. My doctoral training has particularly sensitized me to the transmission of knowledge and pedagogy, skills that I use to make complex technical concepts accessible.
Experience / Qualifications
As a senior technical advisor at Orange, I lead major technological innovation projects and oversee software architecture choices. My expertise has been forged through more than 10 years of software development consulting with major accounts, where I supported the digital transformation of companies in various sectors (telecommunications, finance, industry). This experience has allowed me to master a wide range of technologies and methodologies, from microservices architecture to DevOps practices. At the same time, I founded IM.Coding, a company specializing in custom application development, where we design innovative solutions that meet the highest quality standards. This triple experience - large corporation, consulting, entrepreneurship - gives me a 360° vision of the challenges of modern software development, which I use in my training to prepare developers for the real challenges of the profession.
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
French
English
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
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In the program :

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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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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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Objective: To understand AI without fear, to use it to simplify one's life and to know how to identify digital traps.

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 course is aimed at students and scientists who want to use artificial intelligence to support the writing of academic papers without losing control of the content or compromising academic integrity.

The goal is not to delegate writing to AI, but to learn how to consciously and systematically integrate it into the scientific workflow. Throughout the course, the path from initial idea to final text is explored step by step, always with a critical eye.

We begin with chat setup and formulating appropriate prompts. Good interaction with AI doesn't depend on "tricks," but on clear questions and a well-defined framework. We'll show you how to guide the dialogue to obtain useful and consistent results.

Next, we work on developing the text's structure. AI can help develop a solid and logical outline, which will serve as the basis for subsequent argumentation. We explain how to evaluate and adapt these proposals according to academic criteria.

A central section is dedicated to source research. We analyze how AI can support information retrieval and sorting, and why citation and reference verification is essential. Methods for detecting errors, inaccuracies, and nonexistent sources are presented.

The proper use of footnotes and comments is also addressed. It explains how to integrate references, clarifications, and annotations without sacrificing clarity or formal rigor.

The final phase of the course focuses on writing and revising the text. It demonstrates how to use AI to improve style, coherence, and linguistic precision, as well as to identify argumentative problems. The course concludes with the process of exporting and preparing the final document for submission.

The course is designed for academic work such as essays, coursework, and theses, and is suitable for students of any discipline. No prior technical knowledge is required, only a willingness to work thoughtfully and responsibly.
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