After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
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.
Prerequisites
Curriculum
Course outline
1
Datetimes and Dictionaries
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.
- Representing time with datetimes50 XP
- Creating datetimes for dates100 XP
- Datetimes from strings100 XP
- Converting format with datetimes100 XP
- Working with datetimes50 XP
- Accessing datetime attributes100 XP
- Comparing datetimes100 XP
- Making relative datetimes100 XP
- Dictionaries50 XP
- Creating and accessing dictionaries100 XP
- Accessing safely and deleting100 XP
2
Control Flow and Logic
Through hands-on activities, you’ll discover how to use Boolean logic to determine truth and use comparison and equality operators to control execution in if-statements and loops.
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.
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.
Intermediate Python for Finance
Course
Complete
