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.
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Fundamentals of Machine Learning in Finance
This course is part of Machine Learning and Reinforcement Learning in Finance Specialization
Instructor: Igor Halperin
21,504 already enrolled
Included with
(336 reviews)
Skills you'll gain
- Finance
- Machine Learning Methods
- Data Analysis
- Machine Learning
- Data Science
- Artificial Intelligence and Machine Learning (AI/ML)
- Capital Markets
- Artificial Intelligence
- Computer Science
- Applied Machine Learning
- Unsupervised Learning
- Statistical Machine Learning
- Supervised Learning
- Financial Systems
- Reinforcement Learning
- Financial Market
- Machine Learning Algorithms
- Dimensionality Reduction
- General Finance
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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
Offered by
Recommended if you're interested in Machine Learning
University of Illinois Urbana-Champaign
Università di Napoli Federico II
Coursera Project Network
Politecnico di Milano
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Learner reviews
336 reviews
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- 4 stars
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- 3 stars
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- 2 stars
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Reviewed on Sep 18, 2019
This is a great course, I strongly recommend. However, the assignments take a while to finish.
Reviewed on Sep 10, 2021
I liked the course, but the bugs in the programming assignments are sometimes unbearable.
Reviewed on Jul 24, 2020
Great class, but don't believe the programming assignment time estimates... takes way longer!
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