Projet Simplon - Développeur en Intelligence Artificielle 2023-2024

Project Overview

This repository contains the main validation project for the AI Developer Certification (Développeur en Intelligence Artificielle) from Simplon’s School IA Microsoft program for the 2023-2024 academic year. This project serves as the capstone assessment for candidates pursuing the RNCP Level 6 professional certification (equivalent to Bachelor’s degree level).

Certification Context

Program Background

• Institution: École IA Microsoft by Simplon
• Certification Level: RNCP 37827 - Level 6 (Bac+3/4 equivalent)
• Duration: 19 months total (4 months intensive training + 15 months apprenticeship)
• Recognition: Recognized by France Compétences
• Success Rate: 95.9% overall success rate (48.5% full validation, 47.4% partial validation)
• Employment Rate: 71.10% job placement rate

Target Profile

The AI Developer is primarily an application developer specializing in creating applications that integrate artificial intelligence functionalities such as:

• Chatbots
• Recommendation engines
• Document classification systems
• Prediction models
• Generative AI integrations (ChatGPT, etc.)

Core Competency Blocks

The certification is structured around three main competency blocks:

Block 1: Data Management and Infrastructure

Competencies C1-C6:

• C1. Automate data extraction
• C2. Develop SQL queries for data extraction from databases and big data systems
• C3. Develop data aggregation rules from multiple sources
• C4. [Data processing and preparation]
• C5. Develop APIs for dataset provision
• C6. Organize and conduct technical and regulatory monitoring

Block 2: AI Model Integration and Deployment

Competencies C7-C14:

• C7. Identify pre-existing AI services based on functional requirements
• C8. Configure AI services
• C9. Develop APIs exposing AI models
• C10. Integrate AI model/service APIs into applications
• C11. Monitor AI models using standard and project-specific metrics
• C12. Program automated testing for AI models
• C13. Create continuous delivery pipelines for AI models
• C14. Analyze client application needs integrating AI services

Block 3: Application Development and Maintenance

Competencies C15-C21:

• C15. [Application architecture and design]
• C16. [User interface development]
• C17. Develop technical components and application interfaces
• C18. Automate code testing phases during source versioning
• C19. Create continuous delivery processes for applications
• C20. Monitor AI applications
• C21. Resolve technical incidents

Technical Requirements

Environment Setup

# Virtual environment creation and activation
python -m venv env && source env/bin/activate

# Global environment installation
pip install -r requirements.txt

Important Dependencies

• Gensim compatibility: All scripts using Gensim must run with scipy <= 1.12.0
• Execution context: All make commands executed from project root directory
• Documentation: Check docs/ folder for API and application documentation

Technology Stack

The program emphasizes languages and tools adapted for:

• Application development
• Data manipulation
• Artificial intelligence implementation
• Integration with pre-existing AI models and services

Project Structure and Features

Main Development Areas

1. Data Pipeline Management

   • Automated data extraction and processing
   • Multi-source data aggregation
   • Database and big data system integration

2. AI Model Integration

   • API development for AI model exposure
   • Integration with existing AI services
   • Model monitoring and testing automation

3. Application Development

   • Full-stack application development
   • User interface design and implementation
   • Continuous integration/continuous deployment (CI/CD)

4. Monitoring and Maintenance

   • Application performance monitoring
   • Incident resolution procedures
   • Technical documentation and maintenance

Assessment Methodology

Students are evaluated through:

• Practical Projects: Real-world application development
• Professional Presentation: 90-minute presentation with live demonstration
• Technical Documentation: Comprehensive project portfolio
• Jury Assessment: Professional jury evaluation of competencies

Career Opportunities

Target Positions

• AI Application Developer
• Machine Learning Engineer
• Data Integration Specialist
• AI Solutions Architect
• Chatbot Developer
• Recommendation System Developer

Industry Applications

• Financial services (banks, insurance)
• Retail and e-commerce
• Transportation and logistics
• Healthcare technology
• Corporate AI strategy implementation

Partnership and Innovation

This certification is delivered through a strategic partnership between:

• Microsoft: Providing Azure AI certification and cloud infrastructure expertise
• Simplon: Delivering inclusive, project-based pedagogy and professional training
• Industry Partners: Ensuring curriculum alignment with market needs

Additional Certifications

Students also receive:

• Microsoft Azure Fundamentals (AZ-900)
• Microsoft Azure AI Fundamentals (AI-900)
• Microsoft Azure Data Scientist Associate (DP-100)

Conclusion

This project represents the culmination of a comprehensive AI developer training program that bridges the gap between traditional software development and cutting-edge artificial intelligence implementation. It prepares students for the rapidly evolving AI job market while maintaining strong industry connections and practical, hands-on learning approaches.