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AI Business School

You will:

- Intensively practice and apply AI-driven finance-specific use cases—making AI a daily companion in your workflows and daily job routines.

- Start to use AI technologies into your daily sales activities with hands-on exercises in interactive playgrounds and sandbox environments, increasing your confidence to experiment, iterate, and optimize AI-driven tools and technologies right in the course.

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You will:

- Intensively practice and apply AI-driven finance-specific use cases—making AI a daily companion in your workflows and daily job routines.

- Start to use AI technologies into your daily sales activities with hands-on exercises in interactive playgrounds and sandbox environments, increasing your confidence to experiment, iterate, and optimize AI-driven tools and technologies right in the course.

- Master prompting techniques & discover prompting libraries for different Generative AI models for example to craft high-impact financial forecasts, investor presentations, and risk assessments—unlocking new ways to derive data-driven insights and make informed strategic decisions.

- Get inspired by participating in a project to conceptualize a personalized AI use case for your job role.

Welcome to the unique “Practical AI and prompting for finance professionals” course. Just start your AI journey and discover all the fascinating opportunities opened up for you by Artificial Intelligence.

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What's inside

Syllabus

Job-specific use case training for finance
In this module you will get familiar with as well as try out and practice various finance job-specific AI use cases that are truly relevant to your everyday professional life. You will interact with preconfigured, easy-to-use apps across eight core areas gaining hands-on experience with how AI responds to different inputs. By the end of the module, you will have tangible insights into AI capabilities, access to comprehensive resources detailing the use case areas and 50 finance-specific examples.
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Career center

Learners who complete Practical AI and prompting for finance professionals will develop knowledge and skills that may be useful to these careers:
Risk Manager
A Risk Manager is responsible for identifying, assessing, and mitigating financial and operational risks within an organization. The "Practical AI and prompting for finance professionals" course is highly relevant, providing essential skills to leverage artificial intelligence for more robust risk frameworks. Learners will intensively practice AI-driven finance-specific use cases, particularly those focused on risk assessments, directly applicable to the daily routines of a Risk Manager. By mastering prompting techniques for Generative AI models, professionals can unlock new ways to derive data-driven insights from vast datasets, enabling proactive identification of potential threats and more informed strategic decisions. The course’s hands-on approach to integrating AI technologies into workflows, alongside the opportunity to conceptualize a personalized AI use case, ensures that individuals can design and implement innovative AI solutions to enhance risk monitoring, predictive analytics, and compliance, thereby strengthening an organization's resilience.
Financial Analyst
A Financial Analyst plays a critical role in evaluating financial performance, preparing forecasts, and supporting strategic decisions. This course, "Practical AI and prompting for finance professionals," directly equips learners with the advanced skills to excel in this career. By intensively practicing AI-driven finance-specific use cases, such as crafting high-impact financial forecasts, learners will significantly enhance their analytical capabilities. The curriculum emphasizes mastering prompting techniques for Generative AI models, enabling a Financial Analyst to derive deeper, more accurate data-driven insights from complex financial data. Furthermore, the ability to conceptualize a personalized AI use case for their job role ensures that individuals can innovate and apply AI systematically to improve financial modeling, risk assessments, and investor presentations, making them invaluable assets in any organization.
Hedge Fund Analyst
A Hedge Fund Analyst conducts in-depth research and analysis to identify investment opportunities and support portfolio managers in generating superior returns. The "Practical AI and prompting for finance professionals" course is highly valuable for this intellectually rigorous role. Learners will intensively practice AI-driven finance-specific use cases, directly applicable to sophisticated market surveillance, quantitative analysis, and predictive modeling. Mastering prompting techniques for Generative AI models is crucial, enabling a Hedge Fund Analyst to quickly derive nuanced data-driven insights from vast, complex datasets, craft compelling investor presentations, and perform rapid risk assessments. The course's emphasis on hands-on application and the project to conceptualize a personalized AI use case ensures professionals can design and deploy innovative AI solutions, gaining a significant analytical edge in the highly competitive hedge fund industry. This role typically requires an advanced degree.
Corporate Finance Analyst
A Corporate Finance Analyst focuses on managing a company's financial health, specializing in capital budgeting, valuations, mergers and acquisitions, and financial planning. The "Practical AI and prompting for finance professionals" course directly equips learners with modern tools for this essential role. By intensively practicing AI-driven finance-specific use cases, individuals will gain immediate hands-on experience leveraging AI to enhance complex tasks such as financial modeling, strategic forecasting, and investment appraisals. Mastering prompting techniques for Generative AI models will enable a Corporate Finance Analyst to craft high-impact financial forecasts and risk assessments, unlocking new ways to derive data-driven insights for C-suite decision-making. The project to conceptualize a personalized AI use case further empowers professionals to innovate within corporate finance, designing AI solutions that optimize capital allocation and enhance strategic financial planning.
Portfolio Manager
A Portfolio Manager is entrusted with making strategic investment decisions, aiming to maximize returns while managing risk for clients or institutions. This demanding role benefits immensely from the insights and technical capabilities offered by the "Practical AI and prompting for finance professionals" course. Learners will intensively practice AI-driven finance-specific use cases, directly applicable to market analysis, asset allocation, and performance evaluation. Mastering prompting techniques for Generative AI models is crucial, allowing a Portfolio Manager to craft sophisticated investor presentations and rapid risk assessments, unlocking new ways to derive data-driven insights from complex market conditions. The course's emphasis on hands-on application and designing personalized AI use cases ensures professionals can innovate their analytical processes, leading to more informed strategic decisions and a competitive edge in managing diverse investment portfolios. This role typically requires an advanced degree.
Investment Banker
An Investment Banker advises corporations and governments on complex financial transactions, including mergers, acquisitions, and capital raising. Success in this demanding field hinges on meticulous analysis, persuasive presentations, and strategic decision-making, areas profoundly addressed by the "Practical AI and prompting for finance professionals" course. Learners will gain hands-on experience enhancing daily tasks with AI-powered tools, crucial for accelerating due diligence and valuation processes. Mastering prompting techniques for Generative AI models will enable an Investment Banker to craft high-impact investor presentations and risk assessments swiftly and effectively, unlocking new ways to derive data-driven insights. The project to conceptualize personalized AI use cases for a job role fosters an innovative mindset, helping professionals tailor AI solutions to specific deal challenges. This course specifically prepares individuals to leverage AI for competitive advantage in the fast-paced world of investment banking.
Management Consultant Financial Services
A Management Consultant in Financial Services advises organizations on strategy, operations, and technology, frequently guiding them through complex transformations. The "Practical AI and prompting for finance professionals" course is exceptionally relevant for professionals aiming to excel in this field, particularly given the increasing demand for AI integration across industries. Learners will intensively practice AI-driven finance-specific use cases and master prompting techniques for Generative AI models, enabling precise analysis, strategic recommendations, and high-impact presentations for clients. The ability to conceptualize a personalized AI use case for their job role, translating high-level ideas into structured blueprints for real-world finance challenges, is a core consulting skill. This course empowers a Management Consultant to advise clients on leveraging AI for data-driven insights, enhanced decision-making, and competitive advantage, positioning them as a critical resource for future-proofing financial institutions. This role typically requires an advanced degree.
Treasury Analyst
A Treasury Analyst manages an organization's liquidity, cash flow, and financial risks, ensuring optimal financial health. The "Practical AI and prompting for finance professionals" course provides a significant advantage for aspiring and current Treasury Analysts. Learners will gain immediate hands-on experience with AI-powered tools to enhance daily tasks, particularly in generating accurate cash flow forecasts and managing financial instruments. By mastering prompting techniques for Generative AI models, a Treasury Analyst can craft high-impact financial forecasts, optimizing cash management strategies and hedging activities. The course's focus on integrating AI into daily workflows and making AI a daily companion will enable more efficient execution of tasks and more astute decision-making. Developing a personalized AI use case concept further empowers professionals to innovate within treasury operations, applying AI to complex challenges like liquidity prediction or foreign exchange risk management.
Sales and Trading Analyst
A Sales and Trading Analyst facilitates transactions in financial markets, connecting clients with investment opportunities and executing trades. The "Practical AI and prompting for finance professionals" course is highly relevant, explicitly mentioning starting to use AI technologies in daily sales activities. Learners will gain hands-on experience with AI-powered tools to enhance prospecting, client engagement, and market analysis. Mastering prompting techniques for Generative AI models will enable a Sales and Trading Analyst to quickly generate market insights, synthesize complex data for client presentations, and craft more persuasive communications for investor presentations. The course's emphasis on making AI a daily companion in workflows helps professionals efficiently process information, understand market sentiment, and make more informed, timely strategic decisions in a fast-moving, competitive environment.
Financial Planner
A Financial Planner guides individuals and families in managing their financial resources to achieve life goals, including investments, retirement, and estate planning. The "Practical AI and prompting for finance professionals" course provides a significant advantage for enhancing the planner's analytical and communication toolkit. Learners will discover AI-powered tools to enhance daily tasks, which a Financial Planner can leverage for more efficient client data analysis and personalized financial plan generation. Mastering prompting techniques for Generative AI models can aid in creating tailored financial forecasts and presenting complex information clearly to clients, supporting more informed strategic decisions. The course's practical approach to integrating AI into workflows and the project to conceptualize a personalized AI use case can inspire innovation in client advisory services, improving efficiency and the quality of financial advice provided to clients.
Business Intelligence Analyst Financial
A Business Intelligence Analyst in Financial Services focuses on transforming raw data into actionable insights for strategic and operational decision-making. The "Practical AI and prompting for finance professionals" course provides valuable skills to enhance a Business Intelligence Analyst's capabilities. Learners will gain hands-on experience with AI-powered tools, discovering how to integrate them into daily workflows to automate data processing and enrich analysis. Mastering prompting techniques for Generative AI models will enable a Business Intelligence Analyst to more efficiently derive data-driven insights from complex financial data, supporting the creation of more impactful reports and dashboards. The course's emphasis on finance-specific AI use cases and the design of a personalized AI solution will empower professionals to identify new ways AI can enhance data visualization, trend prediction, and decision support systems within financial contexts.
Financial Product Manager
A Financial Product Manager oversees the entire lifecycle of financial products, from conception and development to launch and iteration, ensuring they meet market needs and business objectives. The "Practical AI and prompting for finance professionals" course provides valuable skills for enhancing strategic thinking around AI-driven product innovation. Learners will intensively practice AI-driven finance-specific use cases, which can inform the design of new features and functionalities for financial products. Mastering prompting techniques for Generative AI models can assist a Financial Product Manager in conducting market research, analyzing competitor offerings, and crafting compelling product specifications by deriving data-driven insights more efficiently. The project to conceptualize a personalized AI use case is particularly relevant, allowing individuals to design blueprints for AI-powered financial solutions, vital for creating innovative and competitive products in a rapidly evolving market.
Data Scientist in Finance
A Data Scientist in Finance uses advanced analytical techniques, machine learning, and statistical modeling to extract insights from vast financial datasets. While the "Practical AI and prompting for finance professionals" course focuses on applying existing AI rather than building models, it offers valuable insights for understanding the practical deployment and user interaction aspects of AI. Learners will gain hands-on experience with AI-powered tools and master prompting techniques for Generative AI models, which are crucial for interpreting outputs and collaborating effectively with business stakeholders. The module on designing finance AI use cases, where individuals conceptualize a blueprint for a finance-specific AI challenge, offers valuable perspective on problem definition and business impact, complementing the technical skills of a Data Scientist. This role typically requires an advanced degree.
Compliance Officer, Financial Services
A Compliance Officer in Financial Services ensures an organization adheres to legal, regulatory, and internal policies, mitigating reputational and financial risks. The "Practical AI and prompting for finance professionals" course is highly relevant for leveraging AI to enhance compliance monitoring and reporting. Learners will intensively practice AI-driven finance-specific use cases, which can be adapted to identify suspicious patterns in transactions or communications, aiding in risk assessments. Mastering prompting techniques for Generative AI models can help a Compliance Officer efficiently analyze regulatory documents, generate comprehensive reports, and derive data-driven insights to proactively address potential breaches. The course's hands-on approach and the project to conceptualize a personalized AI use case empower professionals to design AI solutions for automated policy adherence checks, faster incident response, and improved regulatory oversight, thereby strengthening the compliance framework.
Auditor Financial
An Auditor Financial examines an organization's financial records, internal controls, and processes to ensure accuracy, compliance, and integrity. The "Practical AI and prompting for finance professionals" course may be helpful by introducing foundational AI application skills relevant to modern auditing. Learners will gain hands-on experience with AI-powered tools that an Auditor Financial can leverage to enhance daily tasks such as data analysis, anomaly detection, and review of large datasets. Mastering prompting techniques for Generative AI models may assist in synthesizing financial information, drafting audit reports, and deriving data-driven insights more efficiently from complex financial statements. The course's focus on finance-specific AI use cases and the opportunity to conceptualize a personalized AI solution can inspire innovative approaches to audit planning, risk assessment, and evidence gathering, contributing to more effective and efficient audit engagements.

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Practical AI and prompting for finance professionals.
The definitive benchmark textbook of modern artificial intelligence, rigorously unifying search algorithms, probabilistic reasoning, knowledge representation, and machine learning into an elegant, coherent agent-based framework.
A monumental foundational text establishing the mathematical, algorithmic, and statistical principles of modern deep neural networks, from linear algebra and optimization to convolutional and sequence modeling architectures.
Is widely considered a foundational text in financial modeling, often used in university settings. It provides a comprehensive overview of financial modeling principles and applications using Excel. It is highly valuable for building a solid understanding of core concepts and is an excellent reference tool.
Provides an exceptionally practical, code-first curriculum that guides engineers from end-to-end data preprocessing and traditional regression pipelines to production deep learning models and generative neural networks.
Provides a comprehensive guide to prompt engineering, covering techniques for crafting effective inputs to generative AI models. It's particularly useful for understanding how to obtain reliable and predictable results, which is crucial for both beginners and those looking to deepen their practical skills. This book is valuable as a current reference for anyone working with generative AI.
Delivers an authoritative mathematical foundation in Bayesian inference, graphical models, and statistical learning algorithms, bridging foundational probability theory with rigorous predictive computational modeling.
Guides engineers step-by-step through implementing, training, and fine-tuning complete generative transformer architectures in pure PyTorch, providing crystal-clear low-level insight into modern foundation models.
Provides a comprehensive and up-to-date introduction to the investor relations and financial communication profession. It is designed as an authoritative textbook for those beginning a career in IR, covering communication skills, financial knowledge, legal and regulatory guidelines, and professional standards. It is highly valuable as a primary text for undergraduate and graduate courses and professional development programs.
A definitive guide to financial risk management, this handbook provides in-depth analysis of methods for measuring and managing risk in financial institutions. It covers various types of financial risk and crucial reference for professionals and advanced students in finance.
Presents the foundational treatise on Markov decision processes, temporal-difference learning, and policy gradient methods that underpin autonomous decision-making and modern post-training alignment workflows.
Examines holistic architectural patterns for designing resilient machine learning infrastructure, addressing data pipelines, real-time feature stores, continual learning loops, and production deployment reliability.
This influential book challenges conventional notions of risk and probability by focusing on the impact of rare and unpredictable events ("black swans"). It argues that these events have a disproportionate impact on the world and that we are often ill-equipped to deal with them. It's a provocative read that encourages a different way of thinking about risk and uncertainty.
Aswath Damodaran renowned expert in valuation, and this book comprehensive guide to various valuation models and techniques. It's an invaluable resource for anyone building financial models for valuation purposes, providing deep insights into the drivers of value.
Demystifies practical transformer model implementation through the Hugging Face ecosystem, demonstrating how to fine-tune, optimize, and deploy attention architectures across diverse natural language processing and understanding tasks.
This handbook offers a global perspective on the state-of-the-art thinking and practice in investor relations and financial communication. Featuring contributions from leading scholars and practitioners, it covers contemporary issues, including ESG, corporate governance, shareholder activism, and ethics. It valuable resource for advanced students and professionals seeking in-depth knowledge and a global view of the field.
Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Provides a foundational understanding of risk management and insurance principles, making it ideal for those new to the topic or seeking a broad overview. It covers basic concepts, traditional insurance, and introductory enterprise risk management, serving as a valuable textbook for undergraduate programs and a solid starting point for professionals.
This guidebook offers a comprehensive overview of the Business Intelligence lifecycle, from data integration to analytics. It provides clear explanations of architectural design and processes, making it valuable for gaining a broad understanding of the field. It useful reference for navigating the complexities of BI projects and includes practical solutions.
This McKinsey & Company classic focuses on valuation principles, which are integral to financial modeling. It provides a rigorous framework for valuing companies and understanding the drivers of value. It key resource for anyone involved in corporate finance and valuation.
Focused specifically on operational risk in the financial services industry, this book provides a detailed guide to managing this critical area. It covers frameworks, techniques, and best practices for identifying, assessing, and mitigating operational risks. It's essential for professionals working in risk management within banks and financial institutions.
Aligned with international standards like ISO 31000 and the COSO ERM Framework, this book offers a comprehensive introduction to enterprise risk management. It covers identification, analysis, and treatment of various risks, including emerging trends. It's suitable for students and risk professionals seeking a thorough grounding in ERM principles and practices.
Considered a classic in investing, this book provides timeless principles for successful long-term investing, focusing on value investing and risk management. While not solely focused on IR, understanding the investor's perspective and valuation methods is fundamental for effective investor relations. is essential reading for anyone involved in the financial markets, including IR professionals.
Provides a comprehensive guide to financial modeling in both corporate and project finance contexts. It includes case studies and practical exercises, making it valuable for those focusing on project finance modeling. It covers complex topics with a clear approach.
Delivers battle-tested operational patterns for serving foundation models, addressing GPU cluster throughput, semantic caching, automated evaluation benchmarks, and continuous latency minimization.
This textbook provides a comprehensive treatment of financial risk management, covering market, credit, and operational risks within financial institutions. It's widely used in undergraduate and graduate finance programs and solid resource for understanding the principles and practices of financial risk management.
For those working with Microsoft BI tools like Power BI, SSAS, and Excel, a strong understanding of DAX is essential. is considered a definitive guide to the DAX language, providing in-depth knowledge for creating powerful calculations and data models.
Provides a hands-on approach to prompt engineering with a focus on using the OpenAI API. It's particularly relevant for undergraduate students, graduate students, and working professionals who want to programmatically interact with LLMs. It serves as a practical guide for implementing prompt engineering techniques in applications.
This guide offers practical, day-to-day information for managing an investor relations department effectively. It addresses creating and communicating a company's investment story, dealing with the buy-side and sell-side, and managing disclosure and guidance. useful reference tool for IR professionals and can provide valuable context for students on the practicalities of the role.
Offers a practical, hands-on approach to prompt engineering specifically with ChatGPT. It's an excellent resource for high school and undergraduate students getting started, providing clear examples and exercises. It serves as a useful introductory guide and additional reading to complement foundational AI courses.
Offers a critical look at common risk management practices and argues for more quantitative approaches. It challenges conventional wisdom and provides insights into improving risk assessment and decision-making. It's valuable for both students and professionals looking to refine their risk management methodologies.
Focuses on the creative aspects of prompt engineering and generating diverse language outputs. It's a good fit for students and professionals looking to go beyond basic prompting and explore more advanced techniques for creative content generation. It adds breadth by covering applications in areas like creative writing and podcasting.
Comprehensive guide to the entire Business Intelligence project lifecycle, from planning to deployment. It provides a structured approach to implementing BI solutions and emphasizes understanding business needs and ensuring data quality. It valuable resource for project managers and those involved in BI implementation.
Details an applied architectural methodology for running high-performance open-weights models on local workstations, tackling quantization fidelity, memory bandwidth limits, and prompt assembly trade-offs.
A practical guide specifically focused on financial modeling for project finance. It covers the unique aspects of modeling for large-scale projects and funding strategies. It valuable resource for those working in project finance.
Provides real-world examples and case studies of how organizations have implemented enterprise risk management. It offers practical insights into the challenges and successes of ERM implementation, making it valuable for those involved in establishing or improving an ERM program.
Focuses on mastering financial modeling specifically within the Excel environment. It covers various techniques and best practices for building effective models. It valuable resource for those who rely heavily on Excel for their financial analysis.
This handbook provides a comprehensive guide to the interconnected areas of governance, risk management, and compliance (GRC). It covers frameworks, best practices, and practical guidance for implementing an integrated GRC program. It's a valuable reference for professionals responsible for GRC in their organizations.
Offers a rigorous theoretical foundation for reasoning under uncertainty, combining graph theory and probability distributions to model complex high-dimensional dependencies across autonomous intelligent systems.
Combines financial analysis and modeling with the use of Excel and VBA. It's suitable for those who want to leverage the power of VBA for more advanced modeling and automation. It bridges the gap between theoretical concepts and practical implementation in Excel.
Delves into the principles behind financial modeling, emphasizing data structure, layout optimization, and model auditing. It's a comprehensive resource for understanding the best practices in financial model development.
Provides real-world examples of how companies are using big data and analytics to achieve success. It showcases Business Intelligence in action across various industries, offering practical insights and inspiration. It's valuable for understanding the practical applications of BI.
Explores the art and science of prediction in various fields, from weather forecasting to finance. It examines why some predictions succeed while many fail, emphasizing the importance of probability and understanding uncertainty. It offers valuable lessons for risk managers who rely on forecasting and data analysis.
Delves into practical issues and presents case studies related to the execution of Enterprise Risk Management programs. It provides insights from senior risk management professionals and explores how organizations measure the impact of ERM. It is particularly useful for understanding real-world challenges and best practices in ERM implementation.

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