The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) understanding where the problem one faces lands on a general landscape of available ML methods, (2) understanding which particular ML approach(es) would be most appropriate for resolving the problem, and (3) ability to successfully implement a solution, and assess its performance.
Fundamentals of Machine Learning in Finance
Fundamentals of Machine Learning in Finance
This course is part of Machine Learning and Reinforcement Learning in Finance Specialization
Instructor: Igor Halperin
21,352 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
3.7
(335 reviews)
Intermediate level
Some related experience required
18 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace
Details to know
Shareable certificate
Add to your LinkedIn profile
Taught in English
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This course is part of the Machine Learning and Reinforcement Learning in Finance Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
What's included
9 videos4 readings1 programming assignment1 ungraded lab
What's included
6 videos3 readings1 programming assignment1 ungraded lab
What's included
7 videos3 readings1 programming assignment1 ungraded lab
What's included
11 videos3 readings1 programming assignment1 ungraded lab
Instructor
Instructor ratings
4.0 (26 ratings)Offered by
Recommended if you're interested in Machine Learning
Johns Hopkins University
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3.7
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Showing 3 of 335
AT
5
Reviewed on Aug 9, 2019
Furthered my understanding of how probabilistic models are connected to Machine Learning models. Very happy with the content in this course.
VV
5
Reviewed on Sep 18, 2019
This is a great course, I strongly recommend. However, the assignments take a while to finish.
AT
5
Reviewed on Sep 2, 2019
Great course which covers both theories as well as practical skills in the real implementations in the financial world.
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