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Guided Tour of Machine Learning in Finance

Master machine learning fundamentals in finance through hands-on projects, focusing on supervised learning methods and practical applications.

Master machine learning fundamentals in finance through hands-on projects, focusing on supervised learning methods and practical applications.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Machine Learning and Reinforcement Learning in Finance Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

3.8

(673 ratings)

35,122 already enrolled

Instructors:

English

پښتو, বাংলা, اردو, 2 more

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Guided Tour of Machine Learning in Finance

This course includes

24 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Implement supervised machine learning algorithms for financial applications

  • Develop predictive models using TensorFlow and neural networks

  • Apply machine learning techniques to bank failure prediction

  • Master fundamental ML concepts and their financial applications

  • Understand the distinction between ML in finance versus tech sectors

Skills you'll gain

Machine Learning
Financial Analysis
TensorFlow
Neural Networks
Data Science
Python Programming
Supervised Learning
Statistical Modeling
Bank Failure Prediction

This course includes:

4.4 Hours PreRecorded video

4 assignments, 4 programming assignments

Access on Mobile, Tablet, Desktop

FullTime access

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There are 4 modules in this course

This comprehensive course provides an introduction to machine learning in finance, combining theoretical foundations with practical applications. Students learn supervised machine learning methods, focusing on predicting bank closures through a capstone project. The curriculum covers essential concepts including AI fundamentals, mathematical foundations, TensorFlow implementation, and real-world financial applications.

Artificial Intelligence & Machine Learning

Module 1 · 3 Hours to complete

Mathematical Foundations of Machine Learning

Module 2 · 5 Hours to complete

Introduction to Supervised Learning

Module 3 · 5 Hours to complete

Supervised Learning in Finance

Module 4 · 9 Hours to complete

Fee Structure

Instructor

Igor Halperin
Igor Halperin

3.8 rating

674 Reviews

54,059 Students

4 Courses

Research Professor of Financial Machine Learning at NYU Tandon School of Engineering

Igor Halperin is a former Research Professor of Financial Machine Learning at NYU Tandon School of Engineering, specializing in applying advanced methods from reinforcement learning, information theory, neuroscience, and physics to financial problems. His research focuses on areas such as portfolio optimization, dynamic risk management, and the inference of sequential decision-making processes of financial agents. With extensive industrial experience in statistical and financial modeling, Igor has worked in areas like option pricing, credit portfolio risk modeling, and operational risk modeling. He previously held the position of Executive Director of Quantitative Research at JPMorgan and served as a quantitative researcher at Bloomberg LP. Igor has published widely in finance and physics journals and is a frequent speaker at financial conferences. He is also the co-author of Credit Risk Frontiers, published by Bloomberg LP. Holding a Ph.D. in theoretical high energy physics from Tel Aviv University and an M.Sc. in nuclear physics from St. Petersburg State Technical University, Igor advises several fintech and data science start-ups as well as risk management firms.

Guided Tour of Machine Learning in Finance

This course includes

24 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

3.8 course rating

673 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.