AI for Finance Training in BRICS Corporate Offsite Training Venues

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) is tailored for intermediate-level financial professionals, risk analysts, and AI engineers looking to build and deploy AI-driven solutions for financial automation and fraud detection.

By the end of the course, participants will be able to:

• Understand the impact of AI on financial automation and fraud detection.
• Create AI models designed to detect fraudulent transactions.
• Apply machine learning techniques for real-time risk assessment.
• Deploy AI-enabled systems for ongoing financial monitoring.

This instructor-led live training in BRICS Corporate Offsite Training Venues empowers finance practitioners and IT personnel with the skills to implement Ollama locally. Participants will learn to deploy, configure, and integrate large language models into secure financial workflows, while applying best practices for compliance and automation.

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) is designed for intermediate-level finance professionals, data analysts, risk managers, and AI engineers who wish to harness multimodal AI for risk analysis and fraud detection.

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

• Grasp the application of multimodal AI in financial risk management.
• Analyze both structured and unstructured financial data to detect fraud.
• Implement AI models to identify anomalies and suspicious activities.
• Utilize NLP and computer vision techniques for analyzing financial documents.
• Deploy AI-driven fraud detection models within real-world financial systems.

This instructor-led live training in BRICS Corporate Offsite Training Venues (online or onsite) is designed for finance professionals who wish to use ChatGPT to streamline their workflows and improve their data analysis and reporting capabilities.

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

• Understand the basics of ChatGPT and how it works.
• Use ChatGPT to automate financial tasks such as data entry and report generation.
• Analyze financial data with ChatGPT to gain insights and make informed decisions.
• Develop custom ChatGPT models for specific financial use cases.

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) is aimed at 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.

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

• Understand the fundamentals of prompt engineering in financial applications.
• Leverage AI models for financial forecasting and market sentiment analysis.
• Automate financial reporting and data extraction using AI prompts.
• Develop AI-driven risk assessment models through optimized prompts.
• Ensure compliance and ethical considerations when using AI in finance.

This two-day workshop equips finance teams with the skills to integrate AI and Claude seamlessly into their daily operations. Rather than focusing on theoretical concepts, the programme emphasizes practical application, enabling finance professionals to leverage Claude responsibly for tasks such as analysis, reconciliation, reporting, documentation, stakeholder engagement, and process optimization.

This comprehensive five-day training program is designed to provide participants with an in-depth understanding of how artificial intelligence (AI) is transforming financial systems. By combining theoretical knowledge with practical applications, the course allows participants to explore advanced AI techniques specifically tailored for the financial sector. Upon completion, participants will possess the skills and insights required to effectively utilize AI technologies in key areas such as financial decision-making, risk management, fraud detection, algorithmic trading, customer service, and other critical functions within financial institutions. This course seeks to empower professionals with the expertise needed to navigate the dynamic landscape of AI-driven finance and maintain a competitive edge in an increasingly demanding industry.

Artificial Intelligence is rapidly emerging as the bedrock of contemporary product management, fundamentally altering how we uncover customer needs, define solutions, and make strategic decisions. Much like electricity transformed industry, AI is reshaping the lifecycle of products—how they are constructed, validated, and iterated.

This live, instructor-led training (available online or onsite) is designed for Product Owners, Scrum Masters, and Agile Coaches seeking to grasp how AI can amplify product ownership and fortify decision-making processes.

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

• Grasp the core principles of Artificial Intelligence and distinguish between traditional AI and Generative AI (GenAI).
• Implement the seven preferred stances of a Product Owner (including the newly introduced Orchestrator stance) and leverage AI to enhance each role—such as Visionary, Experimenter, or Customer Representative.
• Excel in effective prompting techniques, viewing AI tools as intelligent collaborators with distinct capabilities.
• Deepen customer insights by creating AI-supported personas for hypothesis testing and discovery, while preserving genuine customer interactions.
• Formulate and articulate a clear product vision using structured frameworks like the 3x3 Framework, utilizing AI to craft and visualize narratives.
• Accelerate prototyping and hypothesis testing with Generative AI tools, such as generating mock-ups or refining product concepts.
• Inform product decisions by using AI tools to analyze, prioritize, and evaluate features based on value, feasibility, and user impact.
• Automate or delegate routine daily tasks (such as email management, stakeholder coordination, and note-taking) via AI, allowing focus on strategic and creative endeavors.
• Facilitate discussions on AI ethics, bias, and data security to ensure responsible and sustainable AI adoption.
• Identify and design high-value AI use cases tailored to specific product and organizational contexts.
• Explore and experiment with approximately 20 different AI tools and models—ranging from productivity assistants and prototyping platforms to generative video, image, and coding solutions.