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Intermediate Python for Finance

4.3+
13 reviews
Intermediate

Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.

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4 Hours15 Videos52 Exercises
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Course Description

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 course, you’ll be the new Python of Wall Street.
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In the following Tracks

Finance Fundamentals in Python

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  1. 1

    Datetimes and Dictionaries

    Free

    In this chapter, you’ll learn how to create and manipulate Python datetime objects to help you identify key financial events, such as Black Friday. You’ll also learn how to store and efficiently look up items using Python dictionaries.

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    Representing time with datetimes
    50 xp
    Creating datetimes for dates
    100 xp
    Datetimes from strings
    100 xp
    Converting format with datetimes
    100 xp
    Working with datetimes
    50 xp
    Accessing datetime attributes
    100 xp
    Comparing datetimes
    100 xp
    Making relative datetimes
    100 xp
    Dictionaries
    50 xp
    Creating and accessing dictionaries
    100 xp
    Accessing safely and deleting
    100 xp
  2. 3

    Pandas Dataframe

    Discover how to create and access DataFrames with pandas using financial data from other data structures, including Dicts, lists, and CSV files. You’ll then uncover additional insights, as you aggregate data across rows or columns, calculate averages, and extend your data using functions.

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  3. 4

    Working with NASDAQ Stock Data

    In this final chapter, you’ll try your hand at working with real-world NASDAQ stock data as you learn how to interpret new data, create masks to filter data, and visualize your findings with plots.

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GroupTraining 2 or more people?

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In the following Tracks

Finance Fundamentals in Python

Go To Track

Datasets

Alphabet stock

Collaborators

Collaborator's avatar
Adel Nehme
Kennedy Behrman HeadshotKennedy Behrman

Data Engineer, Author, Founder

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Don’t just take our word for it

*4.3
from 13 reviews
69%
8%
15%
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  • Sue D.
    about 2 months

    Interesting course with stunning instructor!

  • Anderson K.
    3 months

    A good course to complement Python skills.

  • Oriol C.
    8 months

    I’m Learning a lot

  • Noa S.
    9 months

    Recommend it to anyone seeking to develop their Python knowledge for real world applications

  • Kyaw A.
    10 months

    Cool stuff for python beginner to enter in the Finance industry for analysis.

"Interesting course with stunning instructor!"

Sue D.

"A good course to complement Python skills."

Anderson K.

"I’m Learning a lot"

Oriol C.

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