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Fintech: AI & Machine Learning in the Financial Industry

The University of Texas at Austin via edX

Overview

This is the third in a series of courses on financial technology, also called Fintech. This course provides an overview of machine learning applications in finance.

The course is structured into three main modules. In the first one, we will survey the crowdfunding market. We will talk about equity crowdfunding and P2P or marketplace lending.

In the second module, we will first learn what artificial intelligence is, and the attempts to create machines and algorithms that can replicate, mimic, and replace human activities. We will review the main machine learning tools, starting from measuring the accuracy of predictive models, to basic linear regressions, linear and non linear machine learning models, and deep learning, and their applications in finance. We will also use python to model credit application decisions.

The third module focuses on quantitative investments, roboadvising, and finance in social platforms.

Having a good grasp of machine learning is becoming a necessary skill in the labor market. After you complete this course, you will be able to have a detailed understanding of what machine learning is, and how it is applied in the financial sector.

Financial professionals are often required or encouraged to continue their education to practice their profession. For some associations, this program may be used for Continuing Education Credits. Please check with your local or national organization if the program qualifies.

Syllabus

Week 1: P2P Crowdfunding

- Equity Crowdfunding

- Marketplace Lending

Week 2: Overview of Artificial Intelligence

- Measuring Accuracy

- Overfitting

- Linear Machine Learning Models

Week 3:

- Non-linear Machine Learning Models

- Deep learning

- Credit Modeling

Week 4:

- Robo-advising

- Social Investing

- Quantitative Investing

Taught by

Cesare Fracassi

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