Certified Quantitative Systems Engineer (CQSE)

Complete real-world projects designed by industry experts, covering topics from quantitive-based asset management to trading signal generation. Master AI algorithms for trading.

What you will learn



Quantitative Trading

Estimated 60 hours

Learn the basics of quantitative analysis, including data processing, trading signal generation, and portfolio management. Use Python to work with historical stock data, develop trading strategies, and construct a multi-factor model with optimization.


Basic Quantitative Trading

Learn about market mechanics and how to generate signals with stock data. Work on developing a momentum-trading strategy in your first project.


Advanced Quantitative Trading

Learn the quant workflow for signal generation, and apply advanced quantitative methods commonly used in trading.


Cryptos, Stocks, Indices, and ETFs

Learn about portfolio optimization, and financial securities formed by stocks, including market indices, vanilla ETFs, and Smart Beta ETFs


Factor Investing and Alpha Research

Learn about alpha and risk factors, and construct a portfolio with advanced optimization techniques.


Sentiment Analysis with Natural Language Processing

Learn the fundamentals of text processing, and analyze corporate filings to generate sentiment-based trading signals.


Advanced Natural Language Processing with Deep Learning

Learn to apply deep learning in quantitative analysis and use recurrent neural networks and long short-term memory to generate trading signals.


Combining Multiple Signals

Learn advanced techniques to select and combine the factors you’ve generated from both traditional and alternative data.


Simulating Trades with Historical Data

Learn to refine trading signals by running rigorous back tests. Track your P&L while your algorithm buys and sells.

Certified Quantitative Systems Engineer (CQSE)

Complete real-world projects designed by industry experts, covering topics from quantitive-based asset management to trading signal generation. Master AI algorithms for trading.

What you will learn



Quantitative Trading

Estimated 60 hours

Learn the basics of quantitative analysis, including data processing, trading signal generation, and portfolio management. Use Python to work with historical stock data, develop trading strategies, and construct a multi-factor model with optimization.


Basic Quantitative Trading

Learn about market mechanics and how to generate signals with stock data. Work on developing a momentum-trading strategy in your first project.


Advanced Quantitative Trading

Learn the quant workflow for signal generation, and apply advanced quantitative methods commonly used in trading.


Cryptos, Stocks, Indices, and ETFs

Learn about portfolio optimization, and financial securities formed by stocks, including market indices, vanilla ETFs, and Smart Beta ETFs


Factor Investing and Alpha Research

Learn about alpha and risk factors, and construct a portfolio with advanced optimization techniques.


Sentiment Analysis with Natural Language Processing

Learn the fundamentals of text processing, and analyze corporate filings to generate sentiment-based trading signals.


Advanced Natural Language Processing with Deep Learning

Learn to apply deep learning in quantitative analysis and use recurrent neural networks and long short-term memory to generate trading signals.


Combining Multiple Signals

Learn advanced techniques to select and combine the factors you’ve generated from both traditional and alternative data.


Simulating Trades with Historical Data

Learn to refine trading signals by running rigorous back tests. Track your P&L while your algorithm buys and sells.

Certified Quantitative Systems Engineer (CQSE)

Complete real-world projects designed by industry experts, covering topics from quantitive-based asset management to trading signal generation. Master AI algorithms for trading.

What you will learn



Quantitative Trading

Estimated 60 hours

Learn the basics of quantitative analysis, including data processing, trading signal generation, and portfolio management. Use Python to work with historical stock data, develop trading strategies, and construct a multi-factor model with optimization.


Basic Quantitative Trading

Learn about market mechanics and how to generate signals with stock data. Work on developing a momentum-trading strategy in your first project.


Advanced Quantitative Trading

Learn the quant workflow for signal generation, and apply advanced quantitative methods commonly used in trading.


Cryptos, Stocks, Indices, and ETFs

Learn about portfolio optimization, and financial securities formed by stocks, including market indices, vanilla ETFs, and Smart Beta ETFs


Factor Investing and Alpha Research

Learn about alpha and risk factors, and construct a portfolio with advanced optimization techniques.


Sentiment Analysis with Natural Language Processing

Learn the fundamentals of text processing, and analyze corporate filings to generate sentiment-based trading signals.


Advanced Natural Language Processing with Deep Learning

Learn to apply deep learning in quantitative analysis and use recurrent neural networks and long short-term memory to generate trading signals.


Combining Multiple Signals

Learn advanced techniques to select and combine the factors you’ve generated from both traditional and alternative data.


Simulating Trades with Historical Data

Learn to refine trading signals by running rigorous back tests. Track your P&L while your algorithm buys and sells.