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
This course is part of Machine Learning and Reinforcement Learning in Finance Specialization

Instructor: Igor Halperin
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(337 reviews)
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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
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Reviewed on Sep 2, 2019
Great course which covers both theories as well as practical skills in the real implementations in the financial world.
Reviewed on Sep 10, 2021
I liked the course, but the bugs in the programming assignments are sometimes unbearable.
Reviewed on Jun 27, 2019
Good course with relevant topics, but assignments are not clear sometimes, lack of support with them.
Recommended if you're interested in Data Science
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