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In the last six years, the financial sector has seen an increase in the use of machine learning models in financial, banking and insurance contexts. Data science and advanced analytics teams in the financial and insurance community are implementing these models regularly and have found a place for them in their toolbox.
The success of machine learning, and in particular deep learning in image recognition and natural language processing applications, has created high expectations and their use has rapidly spread to many different areas. The financial sector is no exception and the last six years have seen an increase in these types of models in financial, banking and insurance contexts. Data science and advanced analytics teams in the financial and insurance community are implementing these models regularly and have found a place for them in their toolbox.
In this course, we will first present a review of some of the applications of machine learning and deep learning. We will then illustrate their use in financial applications through concrete examples that we have seen have sparked interest in the industry. Our examples will illustrate how we can add value through ad hoc construction of architectures rather than a simple exercise of replacing classical models with more complex ones, such as multi-layer networks.
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This course was developed by IVADO and Fin-ML as part of a workshop that takes place yearly in Montréal, since 2018. You will be accompanied throughout and given concrete examples by six international experts from both Academia and Industry.
The course is primarily intended for industry professionals and academics with intermediate knowledge of mathematics and programming (ideally Python). Graduate students in data science and quantitative finance (mainly those who are not yet familiar with machine learning and deep learning) may find this content instructive and compelling. The content of this course will also be of great use to whomever uses or is interested in AI, in any other way. Previous experience in the financial industry is not necessary to follow this course.
This course is brought to you by IVADO, Fin-ML and Université de Montréal.
IVADO is a Québec-wide collaborative institute in the field of digital intelligence.
Fin-ML is a nationwide network of researchers working at the intersection of data science, quantitative finance, and business analytics.
Université de Montréal is one of the world’s leading research universities.
At the end of the MOOC, participants should be able to:
These are the topics of each module:
Module 1 - Introduction and Background
Module 2 - Reminder Machine Learning and Deep Learning
Module 3 - GNN in Finance
Module 4 - ESG Evaluation
Module 5 - Portfolio Design using Reinforcement Learning
Module 6 - Conclusion
What is the complete list of speakers for this course?
Manuel MORALES
Rheia KHALAF
Alexandre NGUYEN
Frederik WENKEL
Elham KHERADMAND
Marie-Ève MALETTE
Who can take this course?
Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.
Who can take this course?
Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.