Algebra and Differential Calculus for Data Science
Master essential calculus concepts for data science, from functions and derivatives to optimization, with a focus on practical applications and understanding.
Master essential calculus concepts for data science, from functions and derivatives to optimization, with a focus on practical applications and understanding.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Expressway to Data Science: Essential Math Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Practice working with logarithm properties and graphical representations
Identify continuous and non-continuous functions
Understand derivative calculations and applications
Use derivatives for function graphing
Apply calculus concepts to optimization problems
Skills you'll gain
This course includes:
2.2 Hours PreRecorded video
25 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 6 modules in this course
This course provides a streamlined approach to essential calculus concepts needed for data science. Starting with fundamental algebra and function reviews, it progresses through derivatives, graphing, and optimization techniques. The curriculum focuses on practical applications rather than theoretical proofs, making complex mathematical concepts accessible for data science applications. Students learn through video lectures, quizzes, and hands-on practice problems.
Functions and Algebra Review
Module 1 · 3 Hours to complete
Induction Proofs, Limits and Continuity
Module 2 · 58 Minutes to complete
Definition of a Derivative
Module 3 · 42 Minutes to complete
Product and Chain Rule
Module 4 · 1 Hours to complete
Using Derivatives to Graph Functions
Module 5 · 1 Hours to complete
Finding Maximums and Minimums
Module 6 · 33 Minutes to complete
Fee Structure
Instructor
Faculty Director of Data Science Programs
Dr. Jane Wall is the Faculty Director of the Data Science Graduate Program at the University of Colorado Boulder, a position she has held since 2021. With a unique blend of business acumen and technical expertise, she brings a diverse background to her role. Dr. Wall began her academic journey with undergraduate degrees in Classical Languages and Political Science, followed by two master’s degrees in Mathematics and Applied Mathematics from the University of Georgia. Her professional experience includes significant roles at IBM, where she worked as a software engineer and manager, as well as leadership positions in various software development companies.Dr. Wall returned to academia to earn her Ph.D. in Computational and Applied Mathematics from Rice University, focusing on computational neuroscience. She has developed and taught numerous data science courses, including "Statistical Programming in R" and "Data Science Practicum." At CU Boulder, she oversees both residential and online modes of the Data Science program, which includes innovative courses like "Algebra and Differential Calculus for Data Science" and "Introduction to R Programming and Tidyverse." Dr. Wall's commitment to advancing data science education is evident through her efforts to create robust curricula that prepare students for successful careers in this rapidly evolving field.
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