Applied Data & AI for Fintech

Pre-registration for the Applied Data & AI for Fintech program is now available! Click on the button, and you will be redirected to a form to complete your application. Your application will then be evaluated, and selected candidates will be contacted for the next steps in the selection process. Pre-Registration is open until October 2nd 2026. Applications will be reviewed as they are received, so we encourage you to apply as soon as possible.

Submit a pre-registration request

The Applied Data & AI for Fintech programme is designed for data professionals who already know how to work with SQL and Python and want to take the next step into applied data and AI roles within the financial sector.

What You'll Learn

• Understand and build modern data solutions: Learn how to ingest, govern, model and serve data, from raw sources to business-ready insights, using modern data engineering and analytics practices.
• Diagnose and explain business problems: Apply statistics, segmentation, cohorts and time-based analysis to understand why things change and identify anomalies, drift and root causes.
• Build predictive and prescriptive models: Develop, evaluate and deploy machine learning models and learn how to turn predictions into decisions while considering real-world costs, risks and business outcomes.
• Apply AI to financial use cases: Explore language models, retrieval and AI agents, and learn how to build useful AI solutions over domain-specific information while considering evaluation and governance.
• Work with financial data and domain concepts: Develop an understanding of how data and AI are applied across financial use cases, including credit risk, scorecards, IFRS 9 and financial decision-making.
• Build on Databricks: Gain hands-on experience with a modern data and AI platform, including data governance, MLflow, Unity Catalog, model deployment and monitoring.

Why Choose this program?

• Technology: Learn methods and concepts that remain relevant across technologies and employers – from analytics and statistics to machine learning, AI, deployment and governance.
• Finance: Understand how data and AI are applied in real financial environments, with domain knowledge that gives technical work meaningful business context.
• Databricks: Apply what you learn on a modern data and AI platform, working in the same environment from the beginning of the programme through to the final project.

Who Can Apply?

The programme is designed for data professionals in Luxembourg and the Greater Region who want to move into or progress within data and AI. We particularly welcome women and other underrepresented communities who are looking to develop their technical careers in Luxembourg’s financial and technology ecosystem.

 It is particularly suited to professionals working in areas such as:

• Data Analytics and Business Intelligence
• Data Science
• Analytics Engineering
• Data Engineering
• Other data-related technical roles

• Week 1 - Kick off
• Week 2 - 5: Descriptive Module: Introduction and the analytics lifecycle; Ingestion and governance; Modelling from bronze to gold; Serving the answer  
• Week 6 - 9: Diagnostic and Insurance Module: Statistics for diagnosis; Segmentation and cohorts; How things change over time; Drift, anomaly and root cause
• Week 10 - 13: Predictive and Prescriptive + Fraud Module: Prediction and time; Building the model; Judging and deploying the model; From score to decision
• Week 14 - 17: Cognitive module: Fundamentals of language models; Retrieval; Agents; Evaluation and governance
• Week 18 - 22: Final project: Project preparation; Data and baseline; Build; Deploy and package; Dry run and presentation
• Week 23: Graduation ceremony

• Build modern data solutions from raw data to business-ready insights.
• Turn financial data into actionable insights using statistical and analytical techniques.
• Develop and deploy predictive models that support real-world financial decisions.
• Apply Generative AI and AI agents to practical financial use cases.
• Understand key financial concepts such as credit risk, scorecards and IFRS 9.
• Use Databricks to build, govern and operationalise data and AI solutions.
• Evaluate data and AI solutions through a business lens, considering value, risk, cost and performance.
• Apply responsible AI and data governance principles throughout the solution lifecycle.

The program is delivered in a hybrid course:

• The first and last sessions will be held on site at DLH
• The technical trainings will be held online on Tuesdays and Thursdays