About this Specialization

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Intermediate Level

Basic math including calculus and linear algebra, basic probability theory and statistics, and programming skills in Python.

Approx. 5 months to complete

Suggested 9 hours/week

English

Subtitles: English

What you will learn

  • Check

    Compare ML for Finance with ML in Technology (image and speech recognition, robotics, etc.)

  • Check

    Describe linear regression and classification models and methods of their evaluation

  • Check

    Explain how Reinforcement Learning is used for stock trading

  • Check

    Become familiar with popular approaches to modeling market frictions and feedback effects for option trading.

Skills you will gain

Predictive ModellingFinancial EngineeringMachine LearningTensorflowReinforcement Learning

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Intermediate Level

Basic math including calculus and linear algebra, basic probability theory and statistics, and programming skills in Python.

Approx. 5 months to complete

Suggested 9 hours/week

English

Subtitles: English

How the Specialization Works

Take Courses

A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.

Hands-on Project

Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.

Earn a Certificate

When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

how it works

There are 4 Courses in this Specialization

Course1

Guided Tour of Machine Learning in Finance

3.8
374 ratings
117 reviews
Course2

Fundamentals of Machine Learning in Finance

3.7
176 ratings
32 reviews
Course3

Reinforcement Learning in Finance

3.3
60 ratings
15 reviews
Course4

Overview of Advanced Methods of Reinforcement Learning in Finance

3.5
40 ratings
5 reviews

Instructor

About New York University Tandon School of Engineering

Tandon offers comprehensive courses in engineering, applied science and technology. Each course is rooted in a tradition of invention and entrepreneurship....

Frequently Asked Questions

  • Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • Prerequisites for the specialization are basic math including calculus and linear algebra, basic probability theory and statistics, and some programming skills in Python. For students that are not familiar with Python and IPython / Jupyter notebooks, reference to tutorials are provided as a part of further reading.

More questions? Visit the Learner Help Center.