Investment Management with Python & Machine Learning

This MOOC provides a solid foundation in data science and computational methods applied to the investment sector, with a focus on the latest advancements in portfolio management. Upon completing the four courses, learners will have the tools needed to design and implement effective investment strategies through a deep understanding of theoretical concepts and numerous practical cases based on real-world issues.

You will:

• 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.

The specialisation consists of 4 MOOCs, each requiring 4 weeks of study at an average of 3 hours per week.

MOOC 1 : 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

MOOC 2 : 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

MOOC 3 : 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

MOOC 4 : 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