26 ratings
1,569 already enrolled
Use matplotlib Pyplot to produce a graph to visualize Big-O performance data.
Write and analyze the performance of a Bubble sort function.
Create a Binary Search function and perform Big-O analysis.
In the field of data science, the volumes of data can be enormous, hence the term Big Data. It is essential that algorithms operating on these data sets operate as efficiently as possible. One measure used is called Big-O time complexity. It is often expressed not in terms of clock time, but rather in terms of the size of the data it is operating on. For example, in terms of an array of size N, an algorithm may take N^2 operations to complete. Knowing how to calculate Big-O gives the developer another tool to make software as good as it can be and provides a means to communicate performance when reviewing code with others. In this course, you will analyze several algorithms to determine Big-O performance. You will learn how to visualize the performance using the graphing module pyplot. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Data Science
pyplot
Python Programming
Big-O
algorithm analysis
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Use matplotlib’s Pyplot module to produce a graph to visualize Big-O performance data.
Write a function that returns one element and analyze the Big-O time complexity.
Write a Bubble sort function and analyze its performance.
Implement a Linear Search of an Array and determine its Big-O.
Create a Binary Search function and perform Big-O analysis.
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.
You can download and keep any of your created files from the Guided Project. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.
Guided Projects are not eligible for refunds. See our full refund policy.
Financial aid is not available for Guided Projects.
Auditing is not available for Guided Projects.
At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
More questions? Visit the Learner Help Center.
