Offered by the Motilal Oswal Centre for Capital Markets (MOCCM), IIT Bombay

This module builds a foundational understanding of how AI and data science support modern financial decision-making. By the end, learners understand the scope of data science, Generative AI, and Agentic AI applications in finance and gain initial hands-on exposure to financial analytics and prompting.

This module introduces learners to the foundations, architectures, use cases, and risks of Generative AI and Agentic AI in financial services. Learners understand how these systems are designed, grounded, evaluated, and deployed responsibly in financial applications.

This module enables learners to explore, summarise, and visualise financial data effectively, so they can analyse and communicate insights from financial datasets.

This module introduces practical Machine Learning methods through finance use cases and clarifies how ML and Generative AI can be combined responsibly. Learners gain a working knowledge of ML workflows in financial contexts and understand how Generative AI can augment, but not replace, validated predictive models.

This module provides a practical understanding of financial forecasting techniques and the use of Generative AI for communicating forecast results. Learners understand when forecasting helps, when it can mislead, and how forecast outputs can be translated into clear management narratives.

This module exposes learners to quantitative investing, trading workflows, and the role of LLMs in investment research. Participants understand the foundations of data-driven trading and investment decisions and how LLMs may support the research phase without replacing quantitative validation.

This module connects data science methods with business and product applications in FinTech and introduces participants to modern AI-native tools for rapid product development. Participants understand the FinTech ecosystem, can conceptualise AI-enabled financial products, and gain exposure to tools and workflows used to build and launch MVPs.

This module introduces governance and responsible AI considerations in finance and allows participants to present an integrated, application-oriented project. Participants appreciate the constraints and responsibilities associated with AI in finance and demonstrate their ability to apply the course concepts to a practical use case.