Big-O Time Complexity in Python Code

In the field of data science, mastering the Big-O time complexity is crucial for optimizing algorithms operating on large datasets. In this course, you will delve into the principles of Big-O performance and gain hands-on experience in analyzing algorithms.

• Utilize matplotlib Pyplot to produce visual representations of Big-O performance data, enhancing your ability to communicate and interpret algorithm efficiency.
• Explore the performance of a Bubble sort function, creating and analyzing its efficiency using Big-O notation.
• Implement a Binary Search function and conduct a comprehensive Big-O analysis to gauge its performance on large datasets.

By the end of this course, you will have a solid understanding of Big-O time complexity, enabling you to optimize algorithms and effectively communicate performance metrics to peers and stakeholders.