AI for Finance Training in Copenhagen

This instructor-led, live training in Copenhagen addresses AI governance and strategic risk management within financial services. The curriculum highlights ethical implications, regulatory frameworks, and the construction of effective oversight mechanisms. Participants gain the ability to synchronize AI strategies with both compliance standards and organizational goals.

This instructor-led live training in Copenhagen (delivered online or onsite) is tailored for intermediate-level financial professionals, risk analysts, and AI engineers seeking to build and implement AI-driven solutions for financial automation and fraud detection.

By the conclusion of the training, participants will be capable of:

• Understanding the strategic role of AI in financial automation and fraud prevention.
• Constructing AI models to identify fraudulent transaction patterns.
• Applying machine learning for immediate risk assessment.
• Rolling out AI-powered systems for financial monitoring.

This live, instructor-led program in Copenhagen empowers finance practitioners and IT staff to effectively implement Ollama in local environments. Learners will acquire the skills to deploy, configure, and integrate large language models into secure financial workflows, while adhering to compliance and automation best practices.

This 40-hour programme, AI for Digital Products in Banking, is tailored for intermediate banking professionals in Copenhagen. It focuses on AI-enhanced digital product design, agile development, and data-informed customer experiences. Through practical workshops, participants acquire the essential skills to refine banking products effectively.

Learn how to utilise Copilot for Finance to simplify reporting and increase overall productivity. This instructor-led training in Copenhagen provides professionals with practical AI skills to automate accounting tasks, develop financial reports, and derive valuable insights, thereby enhancing the efficiency of your daily workflow.

This instructor-led training in Copenhagen enables finance professionals to utilise WrenAI for KPI modelling and the design of regulatory-aware dashboards. Participants will develop practical skills in data source integration, ensuring audit compliance, and creating risk management reports to support effective decision-making.

This instructor-led course in Copenhagen empowers professionals to construct LangGraph-based solutions for finance. Learners will develop the skills to implement workflows that comply with regulatory standards, integrate essential data standards, and roll out systems featuring robust governance, observability, and compliance mechanisms.

This instructor-led live training, offered in Copenhagen (online or onsite), is designed for intermediate-level finance professionals, data analysts, risk managers, and AI engineers looking to apply multimodal AI for risk analysis and fraud detection.

By the conclusion of this training, participants will be able to:

• Grasp the practical applications of multimodal AI in financial risk management.
• Interpret both structured and unstructured financial data to uncover fraud.
• Build AI models capable of detecting anomalies and irregular activities.
• Utilize NLP and computer vision technologies for the analysis of financial documents.
• Integrate AI-driven fraud detection solutions into operational financial systems.

This live, instructor-led training, conducted in Copenhagen either online or onsite, is designed for finance professionals looking to harness ChatGPT for workflow efficiency and superior data analysis and reporting.

By the conclusion of this program, attendees will have the capability to:

• Comprehend the core functionality and working principles of ChatGPT.
• Apply ChatGPT to automate financial duties, ranging from data entry to report generation.
• Analyze financial datasets using ChatGPT to derive actionable insights and support sound decision-making.
• Construct specialized ChatGPT models for particular financial scenarios.

This live, instructor-led training Copenhagen (available online or on-site) is designed for intermediate-level finance professionals and fintech developers looking to apply AI-powered prompt engineering techniques to refine financial analysis, risk management, and decision-making.

By the end of the training, participants will be equipped to:

• Grasp the core principles of prompt engineering in financial contexts.
• Utilise AI models to drive financial forecasting and market sentiment analysis.
• Streamline financial reporting and data extraction through AI prompts.
• Create AI-driven risk assessment models via optimised prompting strategies.
• Uphold compliance and ethical standards when deploying AI in finance.

This five-day course in Copenhagen equips finance professionals with advanced analytics, AI-assisted Python, and agentic AI capabilities. Learn to develop intelligent dashboards, optimize GL operations, and design autonomous workflows for financial analysis, reporting, and strategic decision support.

Delve into AI applications in finance at this Copenhagen course. Explore Machine Learning for risk management, fraud detection, and forecasting. Gain insights into AI in banking, regulatory compliance, and generative AI tools. Acquire the skills needed to drive data-driven decisions and innovation.

This intensive five-day workshop is structured to provide attendees with a profound grasp of how artificial intelligence (AI) is transforming the financial landscape. By integrating theoretical concepts with hands-on practice, learners will examine state-of-the-art AI methodologies specifically adapted for the banking and finance industries. Upon completion, participants will possess the capabilities and insights required to apply AI technologies in strategic decision-making, risk oversight, fraud prevention, algorithmic trading, and client support within financial organizations. The primary goal of this course is to arm professionals with the specialized knowledge necessary to navigate the dynamic environment of AI-enhanced finance and maintain a competitive edge in the market.

Artificial Intelligence is increasingly establishing itself as the core of contemporary product management, fundamentally altering how we identify customer needs, formulate solutions, and drive decision-making. Much like the industrial revolution brought about by electricity, AI is redefining the lifecycle of products, from their construction and validation to their continuous evolution.

Designed for Product Owners, Scrum Masters, and Agile Coaches, this instructor-led live training—available both online and onsite—provides a deep dive into how AI can amplify product ownership and fortify decision-making processes.

Upon completion of the course, participants will be equipped to:

• Grasp the core principles of Artificial Intelligence and clearly distinguish between traditional AI and Generative AI (GenAI).
• Implement the seven key stances of a Product Owner, including the newly introduced Orchestrator role, while leveraging AI to reinforce each position, such as the Visionary, Experimenter, or Customer Representative.
• Refine their prompting techniques to engage AI tools as specialized, intelligent collaborators rather than simple utilities.
• Enhance customer insights by developing AI-assisted personas for hypothesis testing and discovery, ensuring that genuine customer engagement remains central to the process.
• Formulate and articulate a distinct product vision by applying structured models like the 3x3 Framework, utilizing AI to refine and visualize these narratives.
• Expedite the prototyping and hypothesis testing phases by using Generative AI to produce mock-ups and conceptual product designs.
• Inform product decisions by employing AI tools to dissect, rank, and assess features based on their value, feasibility, and user impact.
• Streamline or outsource routine administrative duties, such as email management, stakeholder coordination, and note-taking, to concentrate on high-value strategic and creative initiatives.
• Facilitate conversations regarding AI ethics, bias, and data security to guarantee a responsible and sustainable implementation of AI.
• Recognize and craft impactful AI use cases that align with specific product goals and organizational landscapes.
• Experiment with a diverse portfolio of approximately 20 AI tools and models, ranging from productivity aids and prototyping environments to generative video, image, and coding applications.