Learn machine trading analysis from basic to expert level through a practical course with Python programming language.
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Read or download S&P 500® Index ETF prices data and perform machine trading analysis operations by installing related packages and running code on Python IDE.
Define target and predictor algorithm features for supervised regression machine learning task.
Select relevant predictor features subset through univariate filter methods, deterministic wrapper methods and embedded methods.
Implement false discovery rate, family-wise error rate for univariate methods, recursive feature elimination for deterministic wrapper methods and least absolute shrinkage and selection operator for embedded methods.
Extract predictor features transformations through principal component analysis.
This comprehensive Machine Trading Analysis with Python curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
Understand what you need to succeed in this course and determine if it's the right fit for your learning goals
What you need before starting this Machine Trading Analysis with Python course:
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Everything you need to know about this online course, from duration to certification
Course Instructor
Diego Fernandez
Expert instructor with industry experience
Course Language
English
All materials in English
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
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