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Investment Management with Python & Machine Learning


Key learning objectives

  • Learn to code with Python and use existing Python libraries
  • Understanding Machine Learning techniques and their application to financial data
  • Deepen the advanced methods of analysis and modelling applied to large non-financial data sets in investment decisions.

 « Data Science and Machine Learning for Asset Management»

Explore the 4 MOOCs below on offer as part of the Investment Management with Python and Machine Learning Specialisation.
We remind you that each one leads to a Certificate and can be taken independently. You will learn at your own pace and benefit from the expertise of global thought leaders from EDHEC Business School, Princeton University and the finance industry. Learn more


Explore the 4 MOOCs

Introduction to Portfolio Construction and Analysis with Python

  • Gain an intuitive understanding for the underlying theory behind Modern Portfolio Construction Techniques
  • Utilize powerful Python optimization libraries to build scientifically and systematically diversified portfolios
  • Write custom Python code to estimate risk and return parameters
  • Build custom utilities in Python to test and compare portfolio strategies

Advanced Portfolio Construction and Analysis with Python

  • Analyze style and factor exposures of portfolios
  • Implement Black-Litterman portfolio construction analysis
  • Implement robust estimates for the covariance matrix
  • Implement a variety of robust portfolio construction models

Python Machine-Learning for Investment Management

  • Learn the principles of supervised and unsupervised machine learning techniques to financial data sets
  • Utilize powerful Python libraries to implement machine learning algorithms in case studies
  • Understand the basis of logistical regression and ML algorithms for classifying variables into one of two outcomes
  • Learn about factor models and regime switching models and their use in investment management

Python Machine-Learning for Investment Management with Alternative Datasets

  • Learn why alternative data could be useful in financial market applications,
  • Utilizing various types of alternative data to identify behaviour, predict return and asses risks.
  • Perform (alternative) data analysis using Python (and libraries), replicate relevant data analysis sections of seminal academic and practiocioner work.
  • Gain an understanding of advanced data analytics methodologies, visualization and quantitative modeling applied to alternative data in finance


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Tuition fees

Tuition fees

Financial Aid / Scholarship

You can apply for Financial Aid or a Scholarship on Coursera website. You can also view most course materials for free using the audit mode. Learners with Financial Aid or Scholarships in a course will be able to access all of the course content and complete all work required to earn a Course Certificate. Financial Aid and Scholarships only apply to the course that the application was approved for. Learn more.

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