Masters 2 Artificial Intelligence & Data Science
Reach an expert level in production-grade AI. Design advanced machine learning models, master the full lifecycle of complex industrial data, and engineer elite solutions in deep learning and MLOps workflows.
The Master 2 in Artificial Intelligence & Data Science is a specialized postgraduate program designed to transform core technical engineering proficiency into strategic technological leadership. This intensive one-year cycle focuses on the production-grade deployment of intelligent systems, deep machine learning pipeline development, and advanced algorithm design to fuel complex industrial operations.
Students dive deep into the mechanics of neural network architectures, cutting-edge Natural Language Processing (NLP), and robust computer vision systems. By bridging the gap between theoretical modeling and scalable enterprise deployment, the program prepares graduates to navigate the challenges of modern MLOps, containerized workflows, and comprehensive data engineering governance. Participants emerge as elite systems engineers capable of architecting autonomous frameworks and leading breakthrough AI initiatives in a highly competitive global market.
Program Highlight
About Programs
The Master 2 in Data Science & Artificial Intelligence (Data Analyst Path) is a specialized postgraduate program designed to transform technical proficiency into strategic business leadership. This intensive one-year cycle focuses on the advanced extraction, interpretation, and communication of complex data to drive organizational growth.
Students dive deep into the mechanics of Advanced Statistical Analysis, Predictive Modeling, and Automated Business Intelligence. By bridging the gap between raw data and actionable insights, the program prepares graduates to navigate the challenges of modern data governance, ensuring reliability and ethical compliance in every analytical project. Whether architecting sophisticated dashboards or mastering high-level SQL, participants emerge as experts capable of influencing key stakeholders and leading data-driven initiatives in a global market.
Master 2 in Artificial Intelligence & Data Science
Session: 2026- 2027
Typical Program Structure
The Master 2 (M2) program follows an intensive 12-month engineering structure designed to bridge the gap between academic theory and high-level industrial practice. The curriculum is deeply focused on the production-grade deployment of intelligent systems and mastering the full enterprise AI lifecycle.
- Duration: 1 Year (Intensive)
- Total Credits: 60 ECTS
- Structure: Heavily focused on applied engineering and industrial case studies culminating in a Final Capstone Project with real-world experimentation, production deployment metrics, and an oral defense.
Core Curriculum Topics
Foundations & Advanced AI
- Advanced Mathematics for Machine Learning, Highly Optimized Python for AI Pipelines, and Production-Grade Systems Engineering.
Deep Learning & Vision
- Advanced Neural Network Architectures, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Complex Image Processing & Recognition.
NLP & Generative AI
- Transformer Architectures, Large Language Models (LLMs), High-Performance Semantic Search Infrastructure, and Vector Embeddings.
MLOps & Data Engineering
- Containerization and Orchestration (Docker & Kubernetes), Big Data Stream Processing (Apache Spark), Automated Model Deployment, and Continuous Monitoring.
Applied Industry Methods
- Industrial Machine Learning Case Studies, Ethics & Enterprise AI Governance (GDPR & AI Act compliance), and Professional Technical Consulting Strategies.
Curriculum Overview
The Master 2 in Artificial Intelligence & Data Science curriculum is an elite, high-level technical cycle designed to bridge the gap between advanced predictive modeling and enterprise-grade production deployment. Spanning two intensive semesters, the program moves rapidly from deep learning framework mastery and high-performance computing to the industrialization of intelligent systems. Students are trained to architect automated MLOps pipelines, containerized neural networks, and scalable stream processing architectures, ensuring that complex models are built for real-world resilience and impact. This path emphasizes a “Professional First” approach, combining rigorous technical programming in optimized Python, PyTorch, and Docker with a focus on ethical governance and strategic technical leadership, preparing graduates to navigate the sophisticated technology landscapes of 2027 and beyond.
Curriculum Breakdown Summary
The curriculum is engineered to transform students into high-level technical leaders by blending deep mathematical rigor with enterprise-level systems engineering. The program is balanced across five critical technical pillars: Foundations of AI & Math, where students master advanced statistical learning mechanics; Deep Learning & Vision, focusing on complex neural network architectures and recognition systems; NLP & Generative AI, covering transformer deployments and large language models; MLOps & Data Engineering, which prioritizes the industrialization and automation of containerized data pipelines; and Applied Industry Strategy, culminating in an intensive professional capstone project. This 60-ECTS structure ensures that by the end of the intensive 12-month cycle, graduates cannot only build complex algorithmic models but also deploy and monitor them at enterprise scale within secure, ethical governance frameworks.
| Curriculum Component | Focus Area | ECTS Credits |
|---|---|---|
| Technical Core (Sem 1) | Statistics, SQL Mastery, & Python Engineering | 30 Credits |
| Advanced Specialization (Sem 2) | Predictive Modeling & Strategic BI | 20 Credits |
| Professional Development | Ethics, Governance, & Case Studies | 5 Credits |
| Final Capstone (PFE) | Industrial Mission & Final Defense | 5 Credits |
| Total | Full Academic Year | 60 Credits |
Semester 1: Advanced Analytics & Statistical Modeling
The first semester focuses on the technical mastery required to handle complex datasets and perform deep statistical interrogation.
| Category | Course Code | Course Name | Credits |
|---|---|---|---|
| Foundations | DA-501 | Advanced Statistics for Decision Making | 5 Credits |
| SQL Expert | DA-502 | Advanced SQL & Database Architectures | 5 Credits |
| Programming | DA-503 | Python & R for Advanced Data Analysis | 5 Credits |
| BI Strategy | DA-504 | Strategic Business Intelligence Foundations | 5 Credits |
| Visuals | DA-505 | Data Wrangling & Exploratory Analysis | 5 Credits |
| Governance | DA-506 | Data Ethics, GDPR & Regulatory Compliance | 5 Credits |
Semester 2: Intelligence Deployment & Strategic Leadership
The second semester transitions into the communication and industrialization of data, focusing on storytelling and predictive forecasting.
| Category | Course Code | Course Name | Credits |
|---|---|---|---|
| Visual BI | DA-601 | Automated Dashboarding (Power BI/Tableau) | 5 Credits |
| Predictive | DA-602 | Applied Machine Learning for Analysts | 5 Credits |
| Forecasting | DA-603 | Time Series Analysis & Trend Detection | 5 Credits |
| Storytelling | DA-604 | Data Storytelling & Strategic Communication | 5 Credits |
| Professional | DA-605 | Industrial Case Studies & Business Games | 5 Credits |
| Capstone | DA-PFE | Final Project (Professional Mission & Defense) | 5 Credits |
Manel Boumaiza
Data Engineering · NLP · Deep Learning
Ammar Djebabla
Cloud Computing · Distributed Systems
Djihane Houfani
IS Architecture · Enterprise SystemsPrograms Cost
The total tuition for the AI2 Master 2 program (Level 7) 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’s Level 7 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 RNCP Level 7 Master’s 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.