MSc Finance & AI

Campus

  • PARIS
  • THIONVILLE-LUXEMBOURG

Duration

  • 1 year

In Short

Intake

  • February
  • September

Pace

  • Initial

Graduation diploma

  • Niveau Bac+5
  • State-recognized Degree

Teaching languages

  • English English

Tuition fees

  • Septembre intake : €13,000 per year (Paris and Thionville)
  • February intake : €12,000 per year (Paris only)
  • EARLY BIRD! For any registration completed before December 1: €11,500 per year

Contacts

Promotion officier : 
François RAMONET
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Application Brochure

  • Description

  • Programme

  • Career Opportunities

Presentation

The MSc Finance & AI trains experts to combine finance, data and artificial intelligence to support and automate financial decision-making.

The programme develops skills in financial modelling, Python programming, Machine Learning, risk management, algorithmic trading and data analysis.

Students also learn to address governance, ethical and regulatory issues, while developing their ability to manage FinTech projects and innovative solutions.

Admission

Admission requirements:

  • 240 ECTS credits minimum (applicants holding a 4-year degree / Bachelor’s degree equivalent to 240 ECTS)
  • English: proof of English proficiency is required during the application process (TOEIC, TOEFL, IELTS 6.0, etc.).

Contents of your application file

  • CV and cover letter
  • Identity document
  • Copy of degrees and transcripts

The admissions procedure

  • Review of the application
  • Candidate interview (30 minutes)

Contact

Admission services : 

Send message

Tuition fees

  • Septembre intake : €13,000 per year (Paris and Thionville)
  • February intake : €12,000 per year (Paris only)
  • EARLY BIRD! For any registration completed before December 1: €11,500 per year

Learning outcomes

The programme is built around 6 key skills:

  • Financial Analysis & Modelling:
    Master financial statements, asset valuation and strategic portfolio allocation.
  • Data Engineering & AI:
    Develop skills in Python programming, SQL/Cloud databases, and the deployment of Machine Learning and Deep Learning algorithms applied to finance.
  • Algorithmic Trading:
    Understand high-frequency markets and automate trading strategies.
  • Risk Management & Scoring:
    Build predictive models for credit risk, scoring and anomaly detection.
  • Governance, Ethics & Regulation:
    Apply the legal frameworks of the EU AI Act and MiCA regulation, while ensuring model explainability.
  • Leadership & Change Management:
    Lead cross-functional projects and communicate quantitative results to decision-maker

Teaching modules - Semester 1

Semester 1 : Foundations in Finance, Data & Machine Learning (144 heures)

  • Financial Markets & Risk Modeling 
    Understand financial markets, different asset classes and quantitative risk management techniques.
  • Python for Financial Analytics
    Develop programming skills applied to financial data analysis and automation.
  • Machine Learning for Finance
    Apply Machine Learning techniques to financial decision-making and forecasting.
  • Data Engineering & Cloud Computing 
    Master modern financial data infrastructures and Cloud technologies.
  • AI Governance & Financial Regulation
    Understand the regulatory, ethical and governance issues related to the use of artificial intelligence in finance.
  • Financial Econometrics
    Analyse and forecast financial time series using econometric methods.

Teaching Modules - Semester 2

Semester 2 : Advanced AI Applications & Financial Innovation  (120 heures)

  • Algorithmic Trading
    Design, test and optimise quantitative trading strategies.
  • Deep Learning for Finance
    Leverage advanced artificial intelligence models for financial forecasting and textual data analysis.
  • AI Risk & Fraud Analytics
    Apply artificial intelligence techniques to risk management and fraud detection.
  • Blockhain & Digital Assets
    Understand blockchain technologies and decentralised financial ecosystems.
  • Portfolio Management & Robo-Advisory 
    Develop intelligent solutions for portfolio management and wealth management advisory.

Internship and Final Year Project

  • 4- to 6-month internship
  • Final-year project presentation before a panel

Partnerships and Professional Opportunities

  • Co-teaching of modules:
    Direct involvement of industry professionals through real-world case studies.
  • Long-Term Project:
    Student projects assessed by a panel of industry professionals.
  • Site Visits and Immersion:
    Access to innovation labs and trading rooms in Luxembourg.
  • Preferred Recruitment Opportunities:
    4- to 6-month internship.

Target Careers

  • Corporate Finance & Decision Making : 
    Financial Data Analyst, AI-Ehanced Credit Analyst, Financial Engineering Manager.  
  • Asset Management & Trading : 
    Assistant Portfolio Manager, Financial Risk Analyst, Junior Quantitative Analyst.  

 

  • Risk Management & Compliance : 
    AI Risk Manager, Fraud & Anti-Money Laundering (AML) Analyst, RegTech Consultant.
  • FinTech Consulting & Innovation : 
    Finance & Digital Transformation Consultant, AI & Finance Project Manager, FinTech Solutions Architect.