Professional Trader
Quantitative Trading Strategies using Python
Overview
Master systematic, data-driven trading with Python by exploring predictive models, machine learning, and statistical strategies for profitable decision-making.
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45 Hours of Learning
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0.3K+ Learners
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30,000+ GST
Skills You Will Learn
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Data analysis in Python
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Trading algorithm design
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Risk management planning
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Machine learning application
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Predictive model building
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Portfolio optimization
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Quantitative strategy coding
Course Key Highlights
- Learn systematic, rule-based trading approaches
- Explore statistical arbitrage opportunities in markets
- Apply factor investing and smart beta strategies
- Build predictive models using AI and machine learning
- Implement volatility trading strategies with precision
- Backtest strategies using Python for performance insights
- Evaluate risk-adjusted returns effectively
- Gain industry-relevant quantitative trading expertise
Course Time
Includes:
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Self-paced
Modules -
Practical assignments
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Quizzes and assessments
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45 Hours of Learning
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Quantitative Trading Strategies using Python
Learn to design systematic, data-driven trading strategies using statistical models, ML, and backtesting in Python.
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Algorithmic Trading & Strategies using Python
Develop and execute automated trading strategies using Python, with advanced modeling and risk management.
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Leverage NLP and deep learning to extract insights from text data and build AI-driven trading tools.
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FAQs
What is the main focus of this course?
The course focuses on systematic, data-driven trading strategies using Python, covering statistical, machine learning, and backtesting techniques.
Do I need prior programming experience?
While Python knowledge is helpful, the course includes guidance for applying code to trading models.
Will I learn about real-world trading applications?
Yes, examples include statistical arbitrage, factor investing, and volatility strategies.
How is the course delivered?
It is a self-paced module with assignments, quizzes, and 45 hours of total learning content.
Who is this course suitable for?
Professionals and learners interested in quantitative trading, portfolio optimization, and algorithmic execution.
