Introduction to Python for Finance
This course introduces Python for financial analysis.
- 4 hours
- 14 Videos
- 55 Exercises
- 12,351 Participants
- 4,650 XP
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Course Description
The financial industry is increasingly adopting Python for general-purpose programming and quantitative analysis, ranging from understanding trading dynamics to risk management systems. This course focuses specifically on introducing Python for financial analysis. Using practical examples, you will learn the fundamentals of Python data structures such as lists and arrays and learn powerful ways to store and manipulate financial data to identify trends.
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1
Welcome to Python
FreeThis chapter is an introduction to basics in Python, including how to name variables and various data types in Python.
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Arrays in Python
This chapter introduces packages in Python, specifically the NumPy package and how it can be efficiently used to manipulate arrays.
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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.
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Lists
This chapter introduces lists in Python and how they can be used to work with data.
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Visualization in Python
In this chapter, you will be introduced to the Matplotlib package for creating line plots, scatter plots, and histograms.
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1
Welcome to Python
FreeThis chapter is an introduction to basics in Python, including how to name variables and various data types in Python.
-
Lists
This chapter introduces lists in Python and how they can be used to work with data.
-
Arrays in Python
This chapter introduces packages in Python, specifically the NumPy package and how it can be efficiently used to manipulate arrays.
-
Visualization in Python
In this chapter, you will be introduced to the Matplotlib package for creating line plots, scatter plots, and histograms.
-
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.
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Harvard Business School
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Adina Howe
Assistant Professor and Data Scientist
Adina is an Assistant Professor in the College of Engineering at Iowa State University (ISU) in Ames, Iowa. She teaches numerical methods, computational biology, and data science courses in the undergraduate and graduate programs. Her research focuses on using computational tools to help address global grand challenges, such as how to best manage our land and water resources. She loves dogs, board games, and using programming to solve problems that help people.
See MoreCollaborators
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Lore Dirick
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Eunkyung Park
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Sumedh Panchadhar