This course will enable you mastering machine-learning approaches in the area of investment management. It has been designed by two thought leaders in their field, Lionel Martellini from EDHEC-Risk Institute and John Mulvey from Princeton University. Starting from the basics, they will help you build practical skills to understand data science so you can make the best portfolio decisions.



Python and Machine Learning for Asset Management
This course is part of Investment Management with Python and Machine Learning Specialization


Instructors: Claudia Carrone
19,663 already enrolled
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(329 reviews)
What you'll learn
Learn the principles of supervised and unsupervised machine learning techniques to financial data sets
Understand the basis of logistical regression and ML algorithms for classifying variables into one of two outcomes
Utilize powerful Python libraries to implement machine learning algorithms in case studies
Learn about factor models and regime switching models and their use in investment management
Skills you'll gain
- Predictive Modeling
- Financial Modeling
- Portfolio Management
- Feature Engineering
- Statistical Machine Learning
- Business Ethics
- Trend Analysis
- Regression Analysis
- Data Ethics
- Applied Machine Learning
- Supervised Learning
- Risk Management
- Dimensionality Reduction
- Investment Management
- Market Trend
- Machine Learning
- Computer Science
- Unsupervised Learning
- Asset Management
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There are 5 modules in this course
What's included
9 videos5 readings1 assignment1 discussion prompt1 ungraded lab
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8 videos1 reading1 assignment
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8 videos3 readings1 assignment1 discussion prompt
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7 videos4 readings1 assignment
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7 videos2 readings1 assignment
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Reviewed on Apr 9, 2020
The topics covered in this course are really interesting. I learned a great deal by studying various papers covered in this course - Thank you to both instructors!
Reviewed on Dec 7, 2020
Excellent course, very helpful for my research work
Reviewed on May 11, 2022
Very nice course sharing many types of knowledges around data / cleaning / type of data / several algorithms / organised Python coding

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