Learn numpy , pandas , matplotlib , quantopian , finance , and more for algorithmic trading with Python!
InstructorJose PortillaThe curriculum covers rigorous methods such as ETS, EWMA, and ARIMA models using statsmodels to analyze financial data.
Instruction includes Jupyter Notebook assignments that align well with the course objectives and provide practical application.
Editorial course preview
These 2 complementary views highlight concrete, legible examples from the course presentation.
This slide outlines the curriculum progression from core libraries to time series analysis using Python and the statsmodels library, accompanied by a bell curve graphic.
This introductory slide presents instructor Jose Portilla, highlighting his background as an educator for over 200,000 students and a corporate trainer for Fortune 500 financial institutions.
The algorithmic trading modules rely on Quantopian, which is no longer available.
One signal suggests that while early chapters are detailed, the final sections covering trading algorithms appear rushed and utilize outdated tools.
The curriculum aligns with the goal of learning Python for finance, but setup difficulties may affect those without specific environment experience.