Masters 1 in Artificial Intelligence & Data Science
Build your technical core in production-grade data architectures and advanced programming frameworks. This intensive program transitions engineering-minded students from foundational concepts into deep machine learning paradigms and industrial data pipelines.
The Master 1 in Artificial Intelligence & Data Science is an intensive postgraduate program designed for ambitious students holding a Bachelor’s degree (Bac+3) or equivalent quantitative background. It serves as the vital gateway to achieving expert-level proficiency in production-grade intelligent systems.
The core mission of this year is to build the robust software foundations and data architectures that bridge theoretical science with real-world deployment. You will learn to architect efficient data pipelines, explore advanced machine learning frameworks, and master fundamental software engineering practices required to confidently navigate industrial data lifecycles.
Program Highlights
About Program
Our curriculum is meticulously designed to bridge the gap between academic theory and high-level industrial practice . As the foundational year of our graduate track, the Master 1 program focuses on equipping students with advanced core competencies in software engineering, data architecture, and applied statistical modeling . Students transition from basic scripting to mastering the core technologies used in production systems, ensuring they build a rigorous technical launchpad for advanced AI development .
Master 1 in Artificial Intelligence & Data Science
Session: 2026 - 2027
Typical Program Structure
The Master 1 (M1) program follows an intensive technical structure designed to establish deep software engineering and machine learning foundations. The curriculum focuses on developing hands-on competence in building core data architectures, mastering advanced frameworks, and managing industrial data pipelines.
- Duration: 1 Year (Intensive)
- Total Credits: 60 ECTS
- Structure: Heavily focused on applied engineering and hands-on-labs, transitioning core engineering students into advanced programming paradigms that prepare them for deep AI specializations.
Core Curriculum Topics
Data Engineering & Pipelines
- Advanced Python for Data Science, SQL Databases, Data Platform Foundations, and Intro to Big Data Processing (Apache Spark).
Machine Learning Foundations
- Statistical Learning Foundations, Supervised Learning Mechanics (Regression & Classification), Feature Engineering, and Model Selection.
Deep Learning & NLP Intro
- Introduction to Deep Learning Paradigms, PyTorch Basics, Natural Language Processing Fundamentals, and Text Processing Systems.
Cloud & Systems Architecture
- Cloud Computing Deployment (AWS, Azure, GCP), Information Systems Architecture Rigor, Microservices Foundations, and Enterprise IT Governance.
Applied Prototyping & Strategy
- Rapid Prototyping & System Simulation (MATLAB/Simulink), Industrial AI Case Studies, AI Ethics, Data Strategy, and Guided Apprenticeship Portfolios.
Curriculum Overview
The AI2 curriculum is meticulously designed to deliver a balanced, future-focused learning experience that empowers students with both core software architecture and rigorous data competencies. As the foundational year of our graduate track, each Master 1 module is structured to combine core mathematical foundations with intensive hands-on lab sessions and practical coding exercises. By seamlessly integrating engineering theory with project-based development, we prepare students with the concrete technical skills needed to confidently bridge data workflows into next-generation industrial applications.
Curriculum Breakdown Summary
Our curriculum is structured to provide a well-rounded, progressive learning journey that supports both academic excellence and practical skill development.
| Master 1 Core Framework | Required Credits |
|---|---|
| Technical Core Modules | 30 Credits |
| Advanced Architecture & Systems | 15 Credits |
| Industrial Case Studies | 5 Credits |
| Professional Portfolio & Internship | 10 Credits |
| Total | 60 Credits |
Semester 1: Technical Foundations & Core Architecture
This semester focuses on the essential mathematical and engineering pillars required to design high-performance AI. Students bridge the gap between theoretical data science and robust software engineering.
| Category | Course Code | Course Name | Credits |
|---|---|---|---|
| Mathematics | DS-501 | Advanced Mathematics for Machine Learning | 5 Credits |
| Engineering | DS-502 | Production-Grade Python Engineering | 5 Credits |
| Architectures | DS-503 | Neural Networks & CNN Architectures | 5 Credits |
| Vision | DS-504 | Computer Vision & Image Recognition | 5 Credits |
| Big Data | DS-505 | Big Data Architectures (Spark/Hadoop) | 5 Credits |
| Ethics | DS-506 | AI Ethics & Governance (GDPR/AI Act) | 5 Credits |
Semester 2: Advanced AI & Industrial Deployment
The second semester transitions to the industrialization of AI. Students master cutting-edge generative technologies and learn the MLOps practices necessary to deploy and maintain models in enterprise environments.
| Category | Course Code | Course Name | Credits |
|---|---|---|---|
| NLP | DS-601 | Natural Language Processing (NLP) | 5 Credits |
| GenAI | DS-602 | Generative AI & Large Language Models | 5 Credits |
| MLOps | DS-603 | MLOps: Deployment & Monitoring | 5 Credits |
| Infrastructure | DS-604 | Containerization (Docker/Kubernetes) | 5 Credits |
| Professional | DS-605 | Industrial Case Studies & Consulting | 5 Credits |
| Capstone | DS-PFE | Final Project (Thesis & Oral Defense) | 5 Credits |
Manel Boumaiza
Data Engineering · NLP · Deep Learning
Ammar Djebabla
Cloud Computing · Distributed Systems
Djihane Houfani
IS Architecture · Enterprise SystemsProgram Cost
The total tuition for the AI2 Master 1 program for the 2026–2027 academic year is €13,500. This investment covers all core technical modules, access to our high-performance computing labs, personalized career coaching, and industry-led workshops.
Our costs are designed to remain transparent and competitive, ensuring that you receive exceptional value through a modern, practitioner-aligned curriculum. Every student is eligible to build a “Funding Roadmap” to reduce these out-of-pocket costs through our internal scholarship programs or the zero-cost apprenticeship track for the September 2026 intake.
| Fee Component | Amount | Frequency | Remarks |
|---|---|---|---|
| Academic Tuition | €13,500 | Annual | Covers all Master 1 modules and technical labs. |
| Registration & Admin | Included | One-time | Covers enrollment processing and student ID issuance. |
| Lab & Software Access | Included | Annual | Access to high-performance computing and AI dev tools. |
| Career Services | Included | Continuous | Personalized coaching and apprenticeship placement support. |
| Total Investment | €13,500 | Per Year | Final cost for the direct-payment track. |
Apply Now
The transition from a technical background to a specialized Master’s in AI is a significant career move. At AI2, we bridge the gap between academic theory and high-impact industrial application. Whether you are seeking to secure an apprenticeship with a top-tier tech firm, apply for a merit-based scholarship, or utilize public funding for your career transition, our admissions team is here to help you finalize your 2026–2027 funding roadmap. Join a community of practitioners who are defining the future of the field.
Private Funding Track
Ideal for students paying tuition directly. Benefit from our fee-free 10-month payment plan to spread your investment across the academic year with 0% interest and no administrative charges.
Sponsored Track
Join the "contrat d’apprentissage" track to have 100% of your tuition covered by a host company. You graduate with zero debt, two years of experience, and a monthly professional salary.
Requirements and Deadlines
AI2 utilizes a rigorous, evidence-based selection process to identify candidates with the technical foundation and professional maturity required for a high-level career in Artificial Intelligence. As a practitioner-led institute, we prioritize individuals who demonstrate both academic excellence and a tangible passion for shipping real-world AI systems.
Admissions Requirements
1. Academic Qualifications
- Bachelor’s Degree: A state-recognized degree at EQF Level 6 in a quantitative field such as Computer Science, Mathematics, Physics, or Engineering is mandatory for entry into our Level 7 Master’s programs.
- Strong Record: Candidates should demonstrate consistent academic excellence, typically reflected in a "mention bien" or an equivalent international grade.
3. English Language Proficiency
- B2 Level or Higher: Proof of English proficiency is required for international track applicants (TOEFL, IELTS, or equivalent recognized certifications).
- Technical Communication: Candidates must be capable of following high-level technical lectures and collaborating on complex projects entirely in English.
5. Financial & Visa Requirements (International Students)
- Visa Support: Valid passport and compliance with long-stay student visa (VLS-TS) requirements via Campus France.
- Funding Roadmap: Evidence of a sustainable funding plan, which may include AI2 internal scholarships, public grants, or a student loan application.
2. Core Application Materials
- Professional CV: A detailed resume outlining your academic background and any relevant technical or industry experience.
- Transcripts & Certificates: Official documentation of all previous higher education degrees and grades.
- Motivation Letter: A professional statement of purpose detailing your career goals and interest in applied AI.
4. Technical Assessment & Interview
- Technical Portfolio: Submission of a portfolio showcasing personal AI projects, data analysis work, or meaningful open-source contributions is highly encouraged.
- Admissions Interview: Shortlisted candidates will participate in one or two professional interviews with the AI2 faculty to discuss technical aptitude and career aspirations.
Application deadlines for September 2026
The following deadlines apply to our Master 1 programs. We operate a rolling admissions process, and early submission is highly recommended to secure your seat and scholarship eligibility.
| Admission Round | Applications Open | Applications Deadline | Classes Begin |
|---|---|---|---|
| Early Admission Round | April 1, 2025 | December 15, 2025 | September 2026 |
| Regular Admission Round | December 16, 2025 | March 30, 2026 | September 2026 |
| Late Admission Round | April 1, 2026 | June 30, 2026 | September 2026 |
| International Students | 10 Months Before | 6 Months Before | September 2026 |
Apply Now
Choosing where to study Artificial Intelligence is one of the most consequential decisions of your career. At AI2, we ensure that financial barriers do not prevent motivated candidates from reaching their full potential. Whether through our comprehensive scholarship programs, the zero-cost apprenticeship track, or flexible, fee-free payment plans, we work with you to build a funding roadmap that makes industry-leading AI education possible. Join a global cohort of engineers and researchers who are not just learning AI—they are shipping it.
Initial Training Track
Immerse yourself in a full-time academic environment at one of our European campuses. This track is ideal for students focusing entirely on mastering deep technical foundations and production-grade AI systems before entering the global job market.
Apprenticeship Track
Gain critical industry experience while you study through the French "contrat d’apprentissage". Under this regime, your host company covers 100% of your tuition fees, and you receive a monthly professional salary throughout your Master’s program.