Overview

Join over 9 million learners and start Intermediate Python for Finance today!

Are you a financial or business analyst, or simply looking for an easier way to manage your stock portfolio? If so learning Python can automate financial tasks such as calculating risk, mapping market health, and visualizing a stock's price trends, saving you time and money. In this course, you’ll learn how to use Python data structures, execution control statements, and DataFrames to manipulate financial data. You will then work with pandas, using data from the Federal Reserve Bank, to explore national economic trends—an essential part of understanding investment strategies. You will also calculate risk based on stock price data, and display this data in easy to read plots. By the end of this Intermediate Python for Finance course at Data Camp, you’ll be the new Python of Wall Street.

Programme Structure

Chapters include:

Datetimes and Dictionaries

Pandas Dataframe

Control Flow and Logic

Working with NASDAQ Stock Data

Key information

Duration

Part-time
- 1 days

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online

Campus Location

New York City, United States

Disciplines

Finance Software Engineering View 132 other Short Courses in Finance in United States

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Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Prerequisites: Introduction to Python for Finance

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.

International Applies to you

Applies to you

Non-residents

Free
Out-of-State

Free
Domestic

Applies to you

In-State

Free

Additional Details

This course can be accessed for free with the Data Camp Premium or Teams subscriptions

Funding

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Intermediate Python for Finance Data Camp

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