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Villejuif Campus
151 Maxime Gorki Boulevard, 94800 Villejuif
Nice Campus
4 Bd Carabacel, 06000 Nice
Degree RNCP Level 7, equivalent to 6 years of higher education
Entry-level Master’s degree
Duration 12 months
Credits 75 ECTS
Format Work-Study Program, Initial or Continuing Education
Language French
Campus Paris-Villejuif
Back to School October 2027
Program
From Data Masteryto AI Orchestration.
11 seminars, 4 major milestones, 6 Finance AI Products, 2 certifications, the Boarding program, and the AI Clinic.
Academic Background
Four major steps, from the basics to transformation.
Each seminar lists its objective, key concepts, applications, and the associated project, if any.
01
Master & Grow
From financial data to an AI-ready infrastructure.
Before building with AI, you need to master the raw material on which it is based: data. The first three seminars provide the fundamentals needed to understand the technologies, leverage financial data, and master the architectures that power AI solutions.
Objective: To understand how AI and data are already transforming financial industries, processes, and organizations.
Overarching question: Which processes, tasks, and decisions within the Finance function can now be enhanced or transformed by AI?
Objective: To transform financial data into reliable, visualizable, and actionable information.
Comprehensive Preparation: Microsoft Certified: Power BI Data Analyst Associate — PL-300
Finance AI Project #1 — Finance Data & Performance Cockpit: Build a financial management dashboard using data from multiple sources.
Objective: To understand how data flows within the company and to build an architecture capable of powering reliable analytics and AI solutions.
High-performance AI always starts with accessible, reliable, and properly structured data.
Finance AI Project #1 — In-Depth Look: Connecting Data Sources · Data Architecture · Quality · Traceability · Data Preparation.
02
Predict & Build
Moving from data analysis to creating AI solutions.
The "augmented" finance professional must do more than just read data. He or she must be able to anticipate trends, leverage AI models, and turn a use case into a full-fledged business project.
Objective: To learn how to use, compare, and interpret predictive models without becoming a data scientist.
Applications: cash forecasting · budget forecasting · scoring · fraud · accounting anomalies · audit · control · risks.
Finance AI Project #2 — Predictive Finance Engine: Build, compare, and evaluate a predictive solution applied to a financial problem.
Objective: To master generative AI models and learn how to adapt them to the data, documents, and knowledge specific to the Finance function.
Applications: financial analysis · reporting · accounting documents · standards · document audits · contracts · information research · summaries.
Objective: To move from the concept or basic use of a chatbot to a fully-fledged AI solution that can be used within the company.
Finance AI Project #3 — Generative AI Assistant for Finance: Design a specialized assistant capable of leveraging an organization’s data and knowledge to address issues in finance, accounting, auditing, or internal control.
03
Act, Coordinate, & Govern
When AI no longer just responds but begins to take action.
With AI agents, a new milestone has been reached. AI can access tools, interact with systems, perform tasks, and participate directly in financial processes. This opens up considerable potential but also imposes new requirements for control, security, oversight, and accountability.
Objective: To transition from an AI that simply responds to an AI capable of acting in a controlled manner within a business process.
Applications: financial closing · reconciliations · reporting · auditing · billing · collections · control · variance analysis · document collection.
Finance AI Project #4 — Financial AI Agent: Build an agent capable of executing all or part of a financial process in a controlled manner.
Objective: To transition from a standalone agent to an agent-based system integrated into the company.
Comprehensive Preparation: Microsoft Certified: AI Agent Builder Associate
Finance AI Project #5 — Design: Agentic Finance Control Center: Design an agent-based financial system that combines multiple agents, data, tools, and workflows within an orchestrated and monitorable environment.
Objective: To build AI systems capable of being used in a financial environment that places high demands on trust, security, and accountability.
High-performance AI is not enough. It must be secure, governed, controlled, and auditable.
Finance AI Project #5 — Finalization: Transforming the agent-based system into a solution ready for oversight and governance—a true control center that allows us to know what the agents are doing, why, with what data, and when a human needs to take over.
04
Lead, Transform, & Discern
Creating Value with AI and Redefining the Finance Function.
The final step is no longer about learning a new technology. It is about knowing where to use it, how to deploy it, what value to expect from it, and how to reorganize business functions around it.
Objective: To transform an AI opportunity into a realistic, manageable, and value-creating project.
Know how to invest in the right AI projects. But also know when to walk away from those whose cost, risks, or complexity outweigh the value they create.
Finance AI Project #6 — Launch: AI Finance Transformation Blueprint, applied to a real-world problem from the student's professional environment.
Objective: To address both aspects of the same transformation: the process and the role of the professional.
As AI automates production and analysis, finance professionals create greater value through their judgment, decision-making ability, systemic perspective, influence, and ethical responsibility.
Finance AI Project #6 — Finalization: assessment of the current state → AI opportunities → target processes → architecture → people & agents → costs → ROI → risks → governance → roadmap.
Finance AI Product Portfolio
A degree certifies your skills. Your projects demonstrate them.
Throughout the 11 seminars, each student gradually builds a portfolio of six projects focused on finance, accounting, auditing, and internal control. More than just a teaching method, it serves as a true professional showcase.
Finance Data & Performance Dashboard
Build a financial dashboard using data from multiple sources.
Predictive Finance Engine
Build, compare, and evaluate a predictive solution applied to a financial problem.
Generative AI Assistant for Finance
Design a specialized assistant that leverages data and knowledge to address issues in finance, accounting, auditing, or internal control.
Financial AI Agent
Build an agent capable of executing all or part of a financial process in a controlled manner.
Agentic Finance Control Center
Design and then oversee an agent-based financial system that combines agents, data, tools, and orchestrated workflows.
AI Finance Transformation Blueprint
A transformation project based on a real-world challenge faced by the host company.
Learn by building. Build to transform.
Much more than just a program
Four pillars that shape the experience.
Finance AI Product Portfolio
A professional showcase: gain hands-on experience with industry challenges, demonstrate your progress, have tangible achievements to highlight in interviews, and prove your dual expertise in Finance, Data, and AI.
Boarding for aivancity
A 20-hour online preparatory program (in collaboration with LinkedIn Learning), available upon admission: Python, SQL, data manipulation, APIs, and algorithmic logic. No prior programming experience is required for admission.
2 professional certifications
A data certification and an AI certification:
Microsoft Certified: Power BI Data Analyst Associate — PL-300; Microsoft Certified: AI Agent Builder Associate. Recognized proof of practical skills that complement the MSc and the RNCP certification.
The AI Clinic
Work on real-world problems even before graduating: analyze a need, explore a use case, prototype a solution, test its effectiveness, and evaluate its value and risks. A space at the intersection of education, experimentation, and organizational transformation.
Here, AI isn't just learned in class. It's put to the test in the real world.
A comprehensive journey, from the basics to transformation.
The information presented on this page is provided for informational purposes only and is not binding. Given the rapid evolution of artificial intelligence and data, aivancity reserves the right to modify the program content, certifications, terms and conditions, schedule, and fees. The final terms and conditions are those provided at the time of registration.