Python Programming Fundamentals
Develop fluency in writing Python code for finance-based data science projects using Jupyter Notebooks.
Structure & duration
10–20 hours to complete
Online self-paced
Practical Skills Modules can be completed online at your own pace.
Prerequisites
We recommend candidates have familiarity with the principles behind Equity Investments and Financial Statement Analysis content from the Level II CFA curriculum.
Available for Level I and Level II.
Overview of Python Programming Fundamentals
Python is the most popular language for machine learning, artificial intelligence, and big data projects for data science professionals due to its efficiency, versatility, and scalability. Python’s library ecosystem and clear syntax make it both easy to learn and easy to deploy. Overwhelmingly, an increasing number of employers expect their staff to have Python knowledge.
In Python Programming Fundamentals, you will explore the basics of Python and how to use Jupyter Notebooks in order to develop, present, and share data science projects-related to finance. Over the course of this module, you will be guided through a series of videos, knowledge check questions, and projects to quickly build up your coding skills while applying them to dozens of industry-specific examples. After completing this module, you will have the tools to apply what you’ve learned immediately.
Key learning objectives for Python Programming Fundamentals
- Master Python programming fundamentals such as variables, datatypes, loops, functions, and conditional statements.
- Discover how to use Jupyter Notebooks for developing, presenting, and sharing data science projects.
- Leverage key Python libraries such as Pandas for data wrangling and analysis, Matplotlib and Seaborn for data visualization, and Plotly Express for interactive data visualization in a financial context.
- Perform portfolio optimization, run Monte Carlo simulations, and calculate portfolio returns, risks, and Sharpe ratios in Python.
- Obtain real-world financial data using Pandas Data Reader and Yahoo Finance API in Python.
Key learning objectives by unit
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