As artificial intelligence (AI) and machine learning (ML) kick into high gear, many in the financial services industry remain under-equipped to benefit from these technologies. The first step toward the adoption of modern AI is the creation of infrastructure and processes that systematically collect information from within and outside the organization and that facilitate the automation of routine operational as well as analytical tasks.
In this webinar, one can explore how to start this transformation, particularly using Python and databases.
Learning Outcomes:
- Examine the application areas for automation and AI
- Learn how automation is the first building block for ML
- Discuss actual examples of automation in investment management, including
a. routine operational tasks, and
b. analytical/alert systems. - Identify how to get started in your own organization
This is the archived version of a live webinar that took place on 19 November 2020