Investment Management with Python and Machine Learning Specialization
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Investment Management with Python and Machine Learning Specialization
Instructors: Sean McOwen
Included with 
Get in-depth knowledge of a subject
(1,671 reviews)
Beginner level
No prior experience required
2 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
(1,671 reviews)
Beginner level
No prior experience required
2 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
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
Overview
Skills you'll gain
- Asset Management
- Return On Investment
- Social Network Analysis
- Advanced Analytics
- Investment Management
- Web Scraping
- Network Analysis
- Risk Analysis
- Financial Data
- Unstructured Data
- Risk Management
- Data Visualization Software
- Machine Learning
- Portfolio Management
- Text Mining
- Applied Machine Learning
- Financial Modeling
- Financial Analysis
- Market Data
- Financial Market
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
17 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from EDHEC Business School
Specialization - 4 course series
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
Skills you'll gain
Risk Management, Portfolio Management, NumPy, Simulations, Investment Management, Matplotlib, Risk Analysis, Financial Analysis, Probability Distribution, Data Manipulation, Financial Modeling, Asset Management, Pandas (Python Package), and Python Programming
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
Skills you'll gain
Python Programming, Regression Analysis, Risk Management, Financial Market, Risk Analysis, Asset Management, Financial Modeling, Statistical Methods, Return On Investment, Time Series Analysis and Forecasting, Investment Management, Portfolio Management, and Estimation
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
Regression Analysis, Applied Machine Learning, Asset Management, Unsupervised Learning, Portfolio Management, Risk Management, Machine Learning, Feature Engineering, Investment Management, Dimensionality Reduction, Statistical Methods, Supervised Learning, Computer Science, Financial Modeling, and Predictive Modeling
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
Text Mining, Python Programming, Data Analysis, Network Analysis, Market Data, Applied Machine Learning, Risk Analysis, Financial Data, Investments, Social Network Analysis, Unstructured Data, Consumer Behaviour, Financial Analysis, Predictive Analytics, Data Mining, Data Visualization Software, Financial Market, Asset Management, Web Scraping, and Advanced Analytics
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Frequently asked questions
Approximately 4 months to complete
This digital Specialization program is meant to be self-contained and no prior knowledge or Python or portfolio analysis is assumed or required. On the other hand, learners are expected to show a good dose of enthusiasm for, and interest in, the subject of data science applied to investment management.
We encourage you to complete the whole series, starting with “Introduction to portfolio construction and analysis with Python” and “Advanced portfolio construction and analysis with Python”, before taking the “Python Machine-learning for investment management” course. Then, you will be able to put final touch on your understanding of how new data science techniques can be used in investment decisions by taking the course “Python machine-learning for investment management with alternative data sets”.
More questions
Financial aid available,