Course
Introduction to Python for Finance
БазовыйУровень мастерства
Обновлено 04.2026PythonApplied Finance4 ч14 videos54 Exercises4,600 XP100K+Свидетельство о достижениях
Пользуется популярностью среди обучающихся в тысячах компаний.
Обучение двух или более человек?
Попробуйте DataCamp for BusinessОписание курса
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.
Предварительные требования
Для прохождения этого курса не требуется никаких предварительных условий.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
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