Investment Management with Python and Machine Learning Specialization
Instructors: Sean McOwen
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What you'll learn
Write custom Python code and use existing Python libraries to build and analyse efficient portfolio strategies.
Write custom Python code and use existing Python libraries to estimate risk and return parameters, and build better diversified portfolios.
Learn the principles of supervised and unsupervised machine learning techniques to financial data sets
Gain an understanding of advanced data analytics methodologies, and quantitative modelling applied to alternative data in investment decisions
Skills you'll gain
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Specialization - 4 course series
Introduction to Portfolio Construction and Analysis with Python
What you'll learn
Gain an intuitive understanding for the underlying theory behind Modern Portfolio Construction Techniques
Write custom Python code to estimate risk and return parameters
Utilize powerful Python optimization libraries to build scientifically and systematically diversified portfolios
Build custom utilities in Python to test and compare portfolio strategies
Advanced Portfolio Construction and Analysis with Python
What you'll learn
Analyze style and factor exposures of portfolios
Implement robust estimates for the covariance matrix
Implement Black-Litterman portfolio construction analysis
Implement a variety of robust portfolio construction models
Python and Machine Learning for Asset Management
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
Python and Machine-Learning for Asset Management with Alternative Data Sets
What you'll learn
Learn what alternative data is and how it is used in financial market applications.
Become immersed in current academic and practitioner state-of-the-art research pertaining to alternative data applications.
Perform data analysis of real-world alternative datasets using Python.
Gain an understanding and hands-on experience in data analytics, visualization and quantitative modeling applied to alternative data in finance
Skills you'll gain
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Frequently asked questions
Approximately 4 months to complete