Build Python skills to elevate your finance career. Learn how to work with lists, arrays and data visualizations to master financial analyses.
The financial industry uses Python extensively for quantitative analysis, ranging from understanding trading dynamics to risk management systems. This course will show you how to analyze your financial data by building your Python skills.
The first chapter explains how Python and finance go hand in hand. You will then learn Python basics such as printing output, performing calculations, understanding data types, and creating variables.
Next, you’ll cover lists and arrays in Python, exploring how you can use them to work with data. You’ll use the NumPy and Matplotlib packages to manipulate and visualize data.
Finally, you will finish the course by conducting a Python financial analysis on an S&P 100 dataset. Here, you will apply your Python skills to filter lists, summarize sector data, plot P/E ratios in histograms, visualize financial trends, and identify outliers.
By the end of the course, you will be confident in your basic Python skills and practical financial analysis skills. These skills are highly rewarded in the finance industry to solve quantitative finance problems. This course is part of our Finance Fundamentals in Python track which is perfect for those who wish to delve deeper into Python for finance.
The financial industry uses Python extensively for quantitative analysis, ranging from understanding trading dynamics to risk management systems. This course will show you how to analyze your financial data by building your Python skills.
The first chapter explains how Python and finance go hand in hand. You will then learn Python basics such as printing output, performing calculations, understanding data types, and creating variables.
Next, you’ll cover lists and arrays in Python, exploring how you can use them to work with data. You’ll use the NumPy and Matplotlib packages to manipulate and visualize data.
Finally, you will finish the course by conducting a Python financial analysis on an S&P 100 dataset. Here, you will apply your Python skills to filter lists, summarize sector data, plot P/E ratios in histograms, visualize financial trends, and identify outliers.
By the end of the course, you will be confident in your basic Python skills and practical financial analysis skills. These skills are highly rewarded in the finance industry to solve quantitative finance problems. This course is part of our Finance Fundamentals in Python track which is perfect for those who wish to delve deeper into Python for finance.
