Part D explains multi-variable differentiable Calculus is used in Curve Fitting and Error Function. Part C builds upon the Part A and B by introducing basic matrix operations and when matrixes are invertible. Part A and B introduces one variable differentiable Calculus used in Parameter ESTIMATION. If you have not familiar with Python programming, please start with Basics of Python. This module covers basic Linear Algebra and Calculus as it pertains to Machine Learning utilizing Python programming. Please ensure you are utilizing a support browser such as Chrome, Firefox, or Safari. If you have any questions, please reach out to the Luddy Office of Online Education at Required Materials All work is self-graded for individual understanding. No certificates or badges of understanding will be awarded as these are self-graded modules. Modules are designed in text format, some have video content solutions, or answer keys, to each assignment are located within each module under the "Files" tab. You choose which modules you wish to complete and in what order. Since this package is designed for maximum flexiblity, it does not follow a sequential order. Individuals whom purchase the package will have access to the following modules: The Data Science Essentials package is comprised of seven (7) self-paced, or asynchronous, modules specifically created by IU faculty and staff. The promotion code will allow enrollment and entry into the course. Instead, please contact Erin at initiate an internal billing document and obtain a promotion code. Attention IU employees: If university funds will be used for this course registration, do not proceed to PayPal and use a departmental P-card as this is a restricted use of the P-card.
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