After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
Learn the Fundamentals of 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.Manipulate and Visualize Data with Python Packages
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.
Perform Financial Analysis Using Python
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.
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Start Course for FreeWhat you'll learn
- Assess line plots, scatterplots, and histograms produced with Matplotlib’s pyplot to determine suitable visualization methods for communicating financial insights.
- Differentiate Python lists from NumPy arrays to select appropriate data structures for storing and manipulating financial datasets
- Evaluate price-to-earnings ratios and related metrics by applying element-wise operations and NumPy statistical functions to stock data
- Identify fundamental Python syntax elements—variables, data types, and operators—used to perform basic financial calculations
- Recognize correct indexing, slicing, and boolean filtering techniques to extract targeted information from financial lists and arrays
Prerequisites
There are no prerequisites for this course
Curriculum
Course outline
1
Welcome to Python
This chapter is an introduction to basics in Python, including how to name variables and various data types in Python.
2
Lists
This chapter introduces lists in Python and how they can be used to work with data.
3
Arrays in Python
This chapter introduces packages in Python, specifically the NumPy package and how it can be efficiently used to manipulate arrays.
4
Visualization in Python
In this chapter, you will be introduced to the Matplotlib package for creating line plots, scatter plots, and histograms.
5
S&P 100 Case Study
In this chapter, you will get a chance to apply all the techniques you learned in the course on the S&P 100 data.
Introduction to Python for Finance
Course
Complete
