Investment Management with Python and Machine Learning

Open to all, the EDHEC-Risk Institute MOOCs on the Coursera platform are designed to enable you to embrace the power of machine learning and data science technology in asset management.

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A MOOC is an online course dedicated to one specific topic, open to all, and can be completed at your own pace.

The Investment Management with Python and Machine Learning Specialisation includes 4 MOOCs that will allow you to unlock the power of machine learning in asset management.

Starting with the basics, we will help you build practical skills to understand data science so you can make the best portfolio decisions. These four courses combine Python coding skills with real-life applications in the world of finance.

MOOCs are not only an opportunity to master specific career skills, they also give you the chance to tap into a broad community of learners with a rich diversity of backgrounds and cultures.
Click on this video to learn more about our specialisation!

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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.
Make the most of your e-learning journey!

More information on the Specialisation

Introduction to Portfolio Construction and Analysis with Python

Key learning objectives

  • 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 

 Format :Open Enrolment

 Time Commitment :4 weeks / 3 to 7 hours per week 

 Output : Certificate proving that you have mastered the key concepts 

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Advanced Portfolio Construction and Analysis with Python

Key learning objectives

  • 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 

 Format :Open Enrolment

 Time Commitment :4 weeks / 2 to 3 hours per week 

 Output : Certificate proving that you have mastered the key concepts 

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Python Machine-Learning for Investment Management

Key learning objectives

  • 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 

 Format :Open Enrolment

 Time Commitment :5 weeks / 2 to 4 hours per week 

 Output : Certificate proving that you have mastered the key concepts

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Python Machine-Learning for Investment Management with Alternative Datasets

Key learning objectives

  • 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 

 Format :Open Enrolment

 Time Commitment :4 weeks / 2 to 3 hours per week 

 Output : Certificate proving that you have mastered the key concepts

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