Artificial Intelligence (AI) and Machine Learning (ML) are reshaping accounting and finance by automating complex tasks and enhancing data insights. This course examines their applications in financial analysis, reporting, and forecasting. ​The course begins with core AI and ML concepts tailored to accounting and finance, highlighting their relevance, potential applications, benefits, and limitations. Participants are introduced to Python and key machine learning techniques, including regression, classification, clustering, and text analysis.

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The next phase focuses on prompt engineering. Participants learn how to design and refine text prompts to guide Large Language Models (LLMs) such as Dify.AI, POA, ChatGPT, and Google Bard. This enables more effective use of AI tools for financial analysis, forecasting, and reporting. The course also includes hands-on Python exercises, where participants generate code through prompt engineering to implement machine learning models in accounting contexts. ​By the end of the course, participants will have practical skills in prompt engineering and machine learning algorithms for accounting applications. They will be able to integrate these capabilities into AI and ML projects, improving model performance and producing more accurate and relevant outcomes in financial tasks.