AI and GenAI in action
In today's data-driven world, harnessing the power of AI and GenAI is not just advantageous; it's essential for staying competitive and driving innovation. This course is designed to bridge the gap between theoretical knowledge of AI/GenAI and its practical application in various industries.
Throughout this training, we'll delve into the depths of AI and GenAI, exploring how AI algorithms analyse vast amounts of data to unearth valuable insights, and how GenAI can be used to create original content and to harness unknown analytical capabilities in your business.
This module is part of our Data & AI curriculum.
Duration: 3h
Language: Available in English, French, and German. The supporting material is only available in English.
Number of participants: up to 15
Available as intra-company course (i.e. dedicated session on demand)
Course content can be customised on demand under specific conditions.
Objectives
By the end of this training, participants will be able to:
- learn the fundamental principles and methodologies underlying AI and GenAI;
- explore hands-on techniques for effectively implementing AI and GenAI algorithms;
- explore various tools and programming packages to implement work with AI and GenAI;
- develop skills to analyse and interpret the outputs generated by AI and GenAI models.
Content
Fundamentals of AI and GenAI:
- Overview of machine learning algorithms and their applications
- Understanding deep learning and neural networks
Practical hands-on exploration:
- Showcasing machine learning and GenAI tools
Case studies:
- Analysing real-world case studies of AI and GenAI across various industries. Understanding the challenges and successes of AI and GenAI adoption
Tools and resources:
- Overview of AI development tools, platforms
- Overview of GenAI tools and services
Target audience
- Data analysts: professionals responsible for analysing and interpreting data to extract meaningful insights for operational intelligence purposes
- Data scientists: experts in machine learning and AI algorithms who seek to enhance their skills and knowledge in implementing AI and Generative AI solutions
- Operational Intelligence Managers: leaders overseeing operational processes and seeking to leverage AI technologies to optimise efficiency and decision-making
- Business intelligence professionals: individuals involved in gathering, analysing, and presenting data to support business decisions and strategies
- IT professionals: those interested in understanding and implementing AI and Generative AI solutions within their organisation's technological infrastructure
Our lead experts
This training is coordinated by Thierry Kremser, Partner at PwC Luxembourg and Andreas Braun, Managing Director at PwC Luxembourg.
Thierry Kremser is a Partner and Advisory Deputy Leader at PwC Luxembourg, specialising in consulting services for operational companies and the public sector, as well as leading PwC’s AI and GenAI services. With an engineering background from ENSTA Paris Tech, he began his career in technology innovation within the Travel and Telecom industries before moving to Luxembourg in 2001 to focus on IT pre-sales and digital transformation projects for European institutions. Since joining PwC in 2004, Thierry has become a trusted advisor in digital transformation, cloud, cybersecurity, data & AI, and IT strategy, particularly in the non-financial sector, driving large-scale cloud migrations and core activity digitalisation for private and public organisations.
Andreas Braun is a managing director specialising in Artificial Intelligence and data science within technology advisory, focusing on AI and machine learning applications in biometrics, healthcare, and border management. With over 15 years of experience, he leads research and innovation projects in biometrics, applied machine learning, and industrial AI. Previously, he was a principal investigator at the Center for Research in Security and Privacy (CRISP) in Darmstadt, contributing to industry transfer, international collaboration, and biometric standardisation. Andreas holds a doctorate in computer science, has authored over 100 scientific publications and patents, and is certified as a PMP and MSP. He is also a member of the European AI Alliance and has led notable projects including AI-driven customer service chatbots, generative AI for AML and KYC, federated data platforms, AI governance for EU institutions, and AI tools for knowledge management.
