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.
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
What will I get if I purchase a Guided Tutorial?
By purchasing a Guided Tutorial, you'll get everything you need to complete the Guided Tutorial 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.
Are Guided Tutorials available on desktop and mobile?
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Tutorials are not available on your mobile device.
Who are the instructors for Guided Tutorials?
Guided Tutorial 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.
Can I download the work from my Guided Tutorial after I complete it?
You can download and keep any of your created files from the Guided Tutorial. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.
What is the refund policy?
Guided Tutorials are not eligible for refunds. See our full refund policy.
Is financial aid available?
Financial aid is not available for Guided Tutorials.
Can I audit a Guided Tutorial and watch the video portion for free?
Auditing is not available for Guided Tutorials.
How much experience do I need to do this Guided Tutorial?
At the top of the page, you can press on the experience level for this Guided Tutorial to view any knowledge prerequisites. For every level of Guided Tutorial, your instructor will walk you through step-by-step.
Can I complete this Guided Tutorial right through my web browser, instead of installing special software?
Yes, everything you need to complete your Guided Tutorial will be available in a cloud desktop that is available in your browser.
What is the learning experience like with Guided Tutorials?
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.