About This Course#
The Data Science Labs on Multivariable Calculus#
By Kindyl King and Mireille Boutin with Alden Bradford and Julia Long
Welcome to MA29000, The Data Science Labs on Multivariable Calculus! This is a one credit course to accompany Calculus 3, during which you will discover applications of multivariable calculus to data science. You will also practice programming in Python and using Arduino sensors and microprocessors to acquire data.
This course requires no work outside of the lab. There is no homework, no quizzes, no tests, and no exams. All work is performed during the 150 minutes spent in the lab each week. Calculus 3 is a co-requisite for taking this course. MA16290 is a pre-requisite, but it can be waived if you have experience in Pytho
Purdue students: You can earn Honors credit for Calculus 3 by taking this lab. See syllabus for details.
More Information and Contact#
For more information regarding this and the other available Data Science Labs, visit the following link: https://engineering.purdue.edu/~mboutin/Data_Science_labs.html
Contact Professor Boutin at mboutin@purdue.edu if you have any more questions regarding this course.
How to Get Started#
You are reading an interactive Notebook written in the Jupyter language. Jupyter allows for a collection of files to be neatly compiled into a single web-page, such as the one you’re looking at. It also allows you to write and compile Python code.
The application that is used to make these Notebooks is JupyterLab, which is what you’ll be using to interact with and edit the labs.
To access the first lab, you will need to click the “next” arrow at the bottom of this page. Throughout the lab, you will be asked to perform some exercises. You will be writing your answers directly in the Notebook. In other words, you will be editing the lab file. In order to edit the lab, you will need to download the file and open it in JupyterLab.
To download a lab, click on the download icon in the top right of the screen and download the .ipynb file.
Then to edit the lab, open the JupyterLab application. This will bring you to a screen with files and a Table of Contents on the left side and a screen on the right side. If not already open, open the files directory by clicking on the folder icon in the top left corner. Open the Downloads file and double-click the corresponding .ipynb file. The lab will then open and you will be able to edit it.
To turn in the labs, you will have to export the file as a PDF and upload it to Gradescope.
Now you are ready to start the Week 1 Lab (Introduction). Click the “next” arrow at the bottom of this page to navigate to it.
If you have any questions or are experiencing any difficulties during these labs, please ask your TA for assistance. They are happy to help!
Acknowledgements#
The development of this course was supported by Purdue’s College of Engineering Honors Program and Purdue’s Department of Mathematics. We thank Prof. Alina Alexeenko, Prof. Eric Nauman , Prof. Kristina Bross, Prof. Milind Kulkarni, Prof. Uli Walther and Dr. Natasha Duncan for their invaluable input and support. Also thank you to Ben Manning for help making the camera work.