What experience level is required for UTAustinX: Fintech: AI & Machine Learning in the Financial Industry?

This course is aimed at the Intermediate level. Having some basic understanding of the topic will help you get the most out of the curriculum.

How long does it take to complete UTAustinX: Fintech: AI & Machine Learning in the Financial Industry?

The total duration of the course is approximately 4 weeks. Since it is generally self-paced, completion time depends entirely on your learning schedule and availability.

Is this course more theory-focused or project-focused?

This course provides a strong mix of conceptual theory and practical application to ensure a comprehensive understanding of the subject matter.

What careers is this course relevant for?

The skills taught in this course are highly relevant for professionals pursuing roles within Business & Management and adjacent technical fields looking to upskill.

Business & Management

UTAustinX: Fintech: AI & Machine Learning in the Financial Industry

Name: UTAustinX: Fintech: AI & Machine Learning in the Financial Industry
Availability: InStock

This course provides a detailed explanation of machine learning and its applications in finance.

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Essentials (Small Teams)

₹12,510/yr

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Teams

₹33,026/yr

Billed annually • 14-day free trial

EnterpriseFor organizations with 50+ learners

Custom Pricing

Why choose Essentials (Small Teams)?

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1 Academy,16 Self-Paced Courses

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Self-Paced Learning ,Employee Upskilling

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Course Insight

Suitable for intermediate learners. Works well as a continuation after mastering Business & Management fundamentals. It bridges the gap toward advanced, production-level engineering.

Intermediate FriendlySelf-Paced Learning

SKILLS TO
MASTER

Business & Management Basics

Fundamental principles and concepts

Practical Application

Real-world project implementation

Best Practices

Industry standard workflows and guidelines

Problem Solving

Core Concepts

Implementation

Workflow Integration

Optimization

Careers:Backend Developer, Software Engineer, API Developer.

Quick Facts

4 weeks

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What You’ll Learn

The exciting new fintech areas of crowdfunding, robo-advising, financial social platform, and the democratization of trading and investments. .
What machine learning is, and how to use machine learning algorithms. .
How large financial institutions and fintech startups use machine learning to improve their financial products..

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Description

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.

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