About this Course#
The Data Science Labs on Differential and Integral Calculus#
By Alden Bradford and Mireille Boutin with Kindyl King and Naazneen Rana
Welcome to MA16290, The Data Science Labs on Differential and Integral Calculus! This is a one credit course to accompany Calculus 2, during which you will discover applications of differential and integral calculus to data science. You will also learn to program in Python and to use Arduino sensors and microprocessors to acquire data.
This course requires no work outside of the lab. It has no homework, no quizzes, no tests, and no exams. All work is performed during the 150 minutes spent in the lab each week. During that time, our friendly undergraduate instructors are there to assist you and answer all your questions.
Calculus 1 is a pre-requisite and Calculus 2 is a co-requisite for taking this course. No prior experience with Python is necessary.
Purdue students: You can earn Honors credit for Calculus 2 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 get started with this course, click the next arrow at the bottom left of this page to get to the first lab. This lab will explain how to interact with the Notebook, including running code, editing cells, and other useful features that can be used in Jupyter. Throughout the lab, you will be asked to perform some exercises. You will write your answers directly in the Notebook. In other words, you will need to edit the lab file. In order to edit the lab, we recommend downloading the file and opening it in JupyterLab.
To begin editing this lab, click on the download icon in the top right of the screen and download the .ipynb version of Lab 0. After this, 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, double-click lab_0.ipynb, and follow the directions in this lab to begin.
To turn in the labs on Brightspace, you will have to export the file as a PDF. To do this, navigate to File, Save and Export Notebook as, and then click on PDF. This will be further explained in Laboratory 0.
If you have any questions or are experiencing any difficulties during these labs, please ask the instructor for assistance.
Acknowledgements#
The development of this course was supported by Purdue’s College of Engineering 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. Thank you to Julia Long for help with proofreading and formatting.