Data-Driven Investing with Python | Financial Data Science

Become a Data Driven Investor. Make Profitable, Robust, Statistically-Backed Investment Decisions | Quantitative Finance

Created by: Fervent #LearnWithDistinction
Rigorous courses, backed by research, taught with simplicity

Created by: Support from Fervent

What Will I Learn?

• Remove the "guesswork" from your investing forever by learning how to statistically test and validate your investment ideas rigorously on Python
• Discover and master the systematic and scientific Data Driven Investing process that will transform the way you analyse investments forever
• Apply everything you learn using rich, large real world data (without compromising on the mathematical and theoretical integrity of concepts)
• Learn how to leverage incredibly powerful relationships and rigorous Financial Data Science techniques on Python to generate Alpha (seriously)
• Understand why the math works (and why equations work the way they do) - even if your math is weak and if math freaks you out.
• Explore evergreen concepts like Expected Returns, Asset Pricing Models, and Portfolio Construction in unique Financial Data Science settings, leveraging Pandas
• Learn and apply powerful Quantitative Finance techniques including "sorts" to create and design portfolios, regressions to "test for alpha", and much more
• Discover how to quantify risk and returns of individual stocks and investment portfolios, both manually as well as on Python working with real-world data

Requirements

• No prior Finance or Investing knowledge required. We start from the very basics. And transform you into a robust Data Driven Investor.
• Basic coding knowledge is REQUIRED. You don't need to be an 'expert' in Python, but you do need to know the basics (e.g., difference between strings, floats, lists, dictionaries)
• It's okay if math freaks you out. Seriously. Every single equation is explained one variable at a time. We rip it apart to its core, and show you how simple it really is.
• Knowledge of basic statistical analysis is useful but NOT essential. Every relevant statistical test is taught from scratch.
• You'll need a calculator, pen and paper (seriously), and your development environment (e.g. Jupyter Notebooks, Text Editors)
• We work with Jupyter Notebooks in the course, but .py versions of all Python code is available for download.

Target audience

• Individual / retail investors looking to "up" their Financial Analysis game by leveraging the power of Financial Data Science and Python
• Hedge Funds Analysts and Associates looking to master Long-Short / Asset Pricing style Quantitative Finance techniques on Python
• Portfolio Managers wanting to move away from subjective decision making to robust data-driven investment analysis techniques on Python, grounded in the academic and practitioner research
• CFA®, ACA, ACCA students looking to apply familiar concepts in practical, data-driven / financial data science environments
• Current and prospective Analysts and Investment Bankers wanting to gain a solid foundation in data driven investment analysis
• Anyone who's curious about learning and applying Financial Data Science using Python