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Unclaimed ProfileUnlock the power of algorithmic trading and data-driven investing with 'Python for Trading & Investing', a comprehensive course designed by Ricardo Naya. Whether you are an aspiring quantitative analyst, an experienced retail trader looking to automate your strategies, or a finance enthusiast eager to harness the capabilities of modern programming, this course provides a practical entry point. You will dive deep into Python’s robust ecosystem, specifically focusing on essential data analysis libraries such as Pandas, NumPy, and Matplotlib. By learning how to programmatically fetch free historical and real-time financial data from web APIs and online resources, you will eliminate the need for expensive proprietary terminal subscriptions. The course guides you step-by-step through importing, cleaning, manipulating, and visualizing stock market datasets. You will also discover how to construct and test mathematical models that identify market trends, giving you a distinct analytical advantage. By the end of this practical program, you will transition from manual spreadsheet tracking to automated, code-based financial analysis, paving the way for advanced algorithmic execution.
About the creator
Ricardo Naya
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Ricardo Naya is a dedicated educator and quantitative developer who specializes in bridging the gap between computer science and financial markets. With a strong focus on Python for trading and investing, Ricardo helps students unlock the power of automated analysis, algorithmic strategies, and data-driven decision-making. His teaching methodology centers on practical application, taking students beyond theoretical concepts to build real-world financial tools, backtest trading strategies, and analyze market data efficiently. Ricardo believes that modern investing requires a blend of financial literacy and technical proficiency, which is why his courses are structured to be accessible yet technically rigorous. Throughout his educational…Show more
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Program Overview
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Learning format
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Price
Price may change · updated within 1–2 weeks
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What You'll Learn
- Fetch and extract free, high-quality financial historical data and real-time stock prices from online APIs and web sources using Python.
- Master foundational data analysis libraries including Pandas, NumPy, and Matplotlib to manipulate and clean financial datasets.
- Develop custom technical indicators and visual charts to analyze stock market trends and historical price movements.
- Build a structured programmatic framework to calculate key portfolio metrics, risk profiles, and asset returns.
- Optimize investment decision-making processes by replacing manual spreadsheet calculations with automated Python scripts.
- Write clean, modular Python code tailored specifically for financial environments and quantitative research.
Best For
- Retail traders looking to transition from manual spreadsheets to automated data analysis.
- Aspiring quantitative analysts wanting to build a foundation in financial data science.
- Finance professionals who want to reduce costs by replacing expensive terminal subscriptions with Python.
- Programmers seeking to apply their coding skills to the stock market and quantitative research.
Not For
- Individuals with zero interest in learning Python programming or syntax.
- Day traders looking for a 'get rich quick' black-box trading bot rather than analytical skills.
- Advanced quantitative developers looking for high-frequency trading (HFT) infrastructure design.
- Learners who prefer point-and-click software over writing code and debugging.
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