Applied Data & AI for FinTech 2026

  • Duration: 20 weeks 
  • Timeline: October 2026 – April 20
  • Target audience: Data professionals (women and other underrepresented groups)
  • Level: Intermediate / Advanced
  • Focus: Applied Data & AI for FinTech
  • Platform: Databricks
  • Core technologies: SQL · Python · Databricks · Machine Learning · Generative AI
  • Format: Technical training · Hands-on projects · Industry mentorship · Team-based final project
    • Technical training: Tuesdays and Thursdays · 6:00 PM – 8:30 PM · Online
    • In-person sessions: Kick-off and graduation sessions will take place in person; all other training sessions will be delivered online
  • Financed by: Digital Learning Hub Luxembourg, Ministry of Labour and European Social Fund
  • Delivered in partnership with: TBC
  • Cohort: 20 participants
  • Kick-off: 24 October 2026 · 10:00 AM – 2:00 PM ·  · Digital Learning Hub Luxembourg, Belval

Turn your data skills into real-world Data & AI solutions for FinTech.

Luxembourg runs on finance – from funds and banking to insurance and payments. Behind many of the industry’s most important decisions are data pipelines, analytical models and AI systems.

The Applied Data & AI for FinTech programme is designed for women 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.

Over five months, participants will learn how to work with real financial data, build and deploy data and AI solutions, and develop the technical and domain knowledge needed to contribute confidently to modern FinTech environments.

Built on Databricks, the programme connects technology, finance and hands-on application – helping participants move from knowing how to code to being able to build, deploy and defend real data and AI solutions.

The program is financed by Digital Learning Hub, the Ministry of Labour and the European Social Fund and is delivered in partnership with industry stakeholders.

Who is this programme for?

The programme is designed for women data professionals in Luxembourg who want to move into or progress within data and AI.

We particularly welcome women from minority and 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

This is not an introduction to programming. The programme is designed for participants who already have a technical foundation and are ready to apply their skills to more advanced data and AI challenges.

Participants should have:

  • SQL querying (Intermediate): Window functions, performance tuning, etc.
  • Python for Data Analysis (Beginner): NumPy, Pandas, Matplotlib, Seaborn, Plotly and Scikit-Learn
  • Basic understanding of core Data Science concepts

The cohort will bring together 20 participants, creating a community of peers working and developing their careers in the same market.

What will you learn?

The programme combines technology, financial domain knowledge and Databricks throughout every stage of the learning journey.

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.

Technology, Finance & Databricks

The programme brings together three complementary areas throughout the five months.

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.

Learn by building

The programme is designed around hands-on learning and real financial use cases.

Participants will complete practical projects throughout the programme, building a portfolio of work that demonstrates how they can apply data and AI techniques to real-world problems.

Across the five learning blocks, participants will move from understanding what happened, to exploring why it happened, predicting what will happen and what to do, and finally working with AI to understand and interact with information.

Final Project

The programme concludes with a team-based capstone project.

Working in teams of three and supported by an industry mentor, participants will take a real-world brief from initial data and baseline analysis through to building, deploying and presenting their solution.

The final project gives participants the opportunity to:

  • Work with a real-world FinTech challenge
  • Apply data engineering, analytics, machine learning and/or AI skills
  • Build a solution on Databricks
  • Work with an industry mentor
  • Consider governance, evaluation and deployment
  • Present their solution and defend their technical decisions

The project will be presented at the programme graduation, giving participants an opportunity to showcase their work and connect with professionals from the sector.

What will you leave with?

By the end of the programme, you will have:

  1. Practical projects based on real financial data that you can showcase to potential employers
  2. A team-based final project developed with an industry mentor
  3. Hands-on experience with a modern data and AI platform
  4. A stronger understanding of FinTech and financial data use cases
  5. A mentor relationship and a network of up to 20 peers
  6. The technical vocabulary and confidence to communicate your work in technical interviews and professional environments

Ready to take your data career further?

Build on your existing SQL and Python skills, develop practical Data & AI expertise, and learn how to apply it to real financial challenges.

Join a community of women building the future of Data, AI and FinTech in Luxembourg.

APPLY NOW

Sponsored By:

For more information, feel free to reach out directly at letzconnect@we-stem.org.