FeaturedUdemy
Writing Efficient Python Code
4.8(2,529)154k studentsINTERMEDIATEEnglish
Korshub's take
Course Overview
This course focuses on optimizing Python execution to reduce runtime and conserve computational resources. Data scientists will learn to write clean, high-performance code by leveraging Python's native structures, profiling tools, and specialized data libraries.
Who Is This Course For?
Tailored for intermediate data scientists and Python programmers looking to overcome computational bottlenecks and eliminate inefficient design patterns in data workflows.
Key Takeaways
- Code Profiling: Measure and analyze runtime performance to detect code bottlenecks accurately.
- Optimization Techniques: Utilize the Python Standard Library, NumPy, and pandas for faster data processing.
- CPE Credit Opportunity: Eligible for CPE credits upon achieving a score of 70% or higher on the qualified assessment.
About this course
As a Data Scientist, the majority of your time should be spent gleaning actionable insights from data -- not waiting for your code to finish running. Writing efficient Python code can help reduce runtime and save computational resources, ultimately freeing you up to do the things you love as a Data Scientist. In this course, you'll learn how to use Python's built-in data structures, functions, and modules to write cleaner, faster, and more efficient code. We'll explore how to time and profile code in order to find bottlenecks. Then, you'll practice eliminating these bottlenecks, and other bad design patterns, using Python's Standard Library, NumPy, and pandas. After completing this course, you'll have the necessary tools to start writing efficient Python code!
The videos contain live transcripts you can reveal by clicking "Show transcript" at the bottom left of the videos.
The course glossary can be found on the right in the resources section.
To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.
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