Course
Writing Efficient Python Code
IntermediateSkill Level
Updated 01/2026PythonProgramming4 hr15 videos52 Exercises4,000 XP150K+Statement of Accomplishment
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Start Course for FreeWhat you'll learn
- Assess when and how to replace explicit loops with vectorized NumPy array or pandas DataFrame operations for faster computation
- Differentiate between pandas row-iteration methods (iloc, iterrows, itertuples, apply) to select the most performant approach for a given task
- Evaluate code execution time and memory usage by applying %timeit, line_profiler, and memory_profiler outputs
- Identify built-in Python functions, data structures, and modules that provide efficient alternatives to manual implementations
- Recognize scenarios where combinatoric generators, Counter objects, and set operations reduce runtime relative to traditional looping constructs
Prerequisites
Data Types in PythonPython Toolbox1
Foundations for efficiencies
In this chapter, you'll learn what it means to write efficient Python code. You'll explore Python's Standard Library, learn about NumPy arrays, and practice using some of Python's built-in tools. This chapter builds a foundation for the concepts covered ahead.
2
Timing and profiling code
In this chapter, you will learn how to gather and compare runtimes between different coding approaches. You'll practice using the line_profiler and memory_profiler packages to profile your code base and spot bottlenecks. Then, you'll put your learnings to practice by replacing these bottlenecks with efficient Python code.
3
Gaining efficiencies
This chapter covers more complex efficiency tips and tricks. You'll learn a few useful built-in modules for writing efficient code and practice using set theory. You'll then learn about looping patterns in Python and how to make them more efficient.
4
Basic pandas optimizations
This chapter offers a brief introduction on how to efficiently work with pandas DataFrames. You'll learn the various options you have for iterating over a DataFrame. Then, you'll learn how to efficiently apply functions to data stored in a DataFrame.
Writing Efficient Python Code
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FAQs
Will I receive a certificate at the end of the course?
Yes, when you complete this course, you would receive an email with a link to your certificate.
What topics are covered in the course?
This course covers topics such as Python's Standard Library, NumPy arrays, timing and profiling code, set theory, looping patterns in Python, basic pandas optimizations, and more.
Who will benefit from this course?
Any jobs that require working with data or writing code in Python could benefit from this course. This includes jobs like data analyst, data engineer, and software developer.
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