AI for Finance Training in Prague

This live, instructor-led training in Prague focuses on AI governance and strategic risk management within financial services. It emphasizes ethical implications, regulatory frameworks, and the establishment of effective oversight mechanisms. Participants will learn to synchronize AI strategies with compliance mandates and organizational goals.

This live, instructor-led training in Prague (available online or onsite) targets intermediate-level financial professionals, risk analysts, and AI engineers who want to build and deploy AI-driven solutions for financial automation and fraud detection.

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

• Comprehend the impact of AI on financial automation and fraud detection.
• Develop AI models specifically designed to identify fraudulent transactions.
• Utilize machine learning for real-time risk evaluation.
• Implement AI-powered systems for financial monitoring.

This instructor-led live training in Prague empowers finance practitioners and IT personnel to implement Ollama locally. Learners will acquire the ability to deploy, configure, and integrate large language models into secure financial workflows, while adhering to compliance and automation best practices.

AI for Digital Products in Banking is a 40-hour course located in Prague, tailored for intermediate banking professionals. It explores the design of AI-enhanced digital products, agile development practices, and data-centric customer experiences. Through practical workshops, participants will acquire the skills needed to refine banking products effectively.

Explore how to utilize Copilot for Finance to simplify reporting and elevate productivity. This instructor-led training held in Prague empowers professionals with practical AI skills to automate accounting tasks, draft financial reports, and extract actionable insights, thereby streamlining your daily workflow.

This instructor-led training in Prague enables finance professionals to utilize WrenAI for KPI modeling and the creation of regulatory-compliant dashboards. Learners will develop practical skills in integrating data sources, ensuring audit compliance, and constructing risk management reports to drive effective decision-making.

This instructor-led training in Prague empowers professionals to design effective LangGraph-based financial solutions. Participants will learn to implement workflows that comply with regulatory requirements, integrate standardized data, and deploy systems equipped with robust governance, observability, and compliance controls.

This instructor-led live training in Prague (online or onsite) is aimed at intermediate-level finance professionals, data analysts, risk managers, and AI engineers who wish to leverage multimodal AI for risk analysis and fraud detection.

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

• Understand how multimodal AI is applied in financial risk management.
• Analyze structured and unstructured financial data for fraud detection.
• Implement AI models to identify anomalies and suspicious activities.
• Leverage NLP and computer vision for financial document analysis.
• Deploy AI-driven fraud detection models in real-world financial systems.

This instructor-led, live training in Prague (online or onsite) is designed for finance professionals aiming to streamline their workflows and enhance their data analysis and reporting capabilities using ChatGPT.

Upon completing this training, participants will be able to:

• Grasp the fundamentals of ChatGPT and its operational principles.
• Leverage ChatGPT to automate financial tasks, such as data entry and report generation.
• Analyze financial data with ChatGPT to extract insights and support informed decision-making.
• Create custom ChatGPT models tailored to specific financial use cases.

This instructor-led, live training in Prague (online or onsite) targets intermediate-level finance professionals and fintech developers who wish to use AI-powered prompt engineering techniques to enhance financial analysis, risk management, and decision-making.

Upon completion of this training, participants will be able to:

• Comprehend the core principles of prompt engineering within financial applications.
• Utilize AI models for financial forecasting and market sentiment analysis.
• Automate financial reporting and data extraction through AI prompts.
• Create AI-driven risk assessment models via optimized prompts.
• Address compliance and ethical considerations when applying AI in finance.

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

Delve into the intersection of AI and finance in this Prague location course. Discover Machine Learning applications essential for risk management, fraud detection, and forecasting. Gain insight into AI's role in banking, regulatory compliance, and generative AI tools. Acquire the skills needed to drive data-driven decision-making and foster innovation.

This extensive five-day training course is crafted to provide participants with a profound comprehension of how artificial intelligence (AI) is transforming financial infrastructure. Combining theoretical foundations with hands-on practice, attendees will investigate state-of-the-art AI methodologies tailored for the finance industry. Upon completion, participants will possess the necessary skills and insights to effectively utilize AI technologies across various domains, including financial decision-making, risk management, fraud detection, algorithmic trading, customer service, and other vital functions within financial organizations. The program seeks to empower professionals with the expertise required to navigate the dynamic world of AI-driven finance and maintain a competitive edge in an increasingly demanding market.

Artificial Intelligence is swiftly establishing itself as the cornerstone of contemporary product management, fundamentally altering the way we uncover customer requirements, craft solutions, and drive decision-making processes. Much like electricity transformed industrial capabilities, AI is redefining the lifecycle of products—from their creation and validation to their continuous evolution.

Designed for Product Owners, Scrum Masters, and Agile Coaches, this instructor-led live training (available online or on-site) focuses on harnessing the power of AI to elevate product ownership and reinforce strategic decision-making.

Upon completion, participants will be equipped to:

• Grasp the core principles of Artificial Intelligence and clearly distinguish between conventional AI systems and Generative AI (GenAI).
• Leverage AI to enhance the seven key stances of a Product Owner—including the emerging Orchestrator role—such as acting as a Visionary, Experimenter, or Customer Representative.
• Develop proficiency in effective prompting techniques, viewing AI tools as capable collaborators with distinct specialized capabilities.
• Deepen customer insights by generating AI-assisted personas for hypothesis testing and discovery, ensuring that authentic engagement with end-users remains a priority.
• Formulate and articulate a coherent product vision using structured methodologies like the 3x3 Framework, while utilizing AI to refine and visualize key narratives.
• Accelerate the prototyping and hypothesis testing phases by employing Generative AI tools to produce mock-ups and conceptual product models.
• Inform product decisions by using AI to analyze, prioritize, and assess features based on criteria such as value, technical feasibility, and user impact.
• Optimize daily workflows by automating or delegating routine tasks—such as email management, stakeholder communication, and meeting notes—to AI, thereby freeing up time for strategic and creative initiatives.
• Facilitate informed discussions on AI ethics, algorithmic bias, and data security to guarantee responsible and sustainable implementation.
• Identify and architect high-value AI use cases that align with specific product goals and organizational contexts.
• Explore and experiment with approximately 20 distinct AI tools and models, ranging from productivity assistants and prototyping platforms to generative solutions for video, image, and code.