Integral Calculus and Numerical Analysis for Data Science
Master essential integral calculus and numerical methods for data science applications with practical focus.
Master essential integral calculus and numerical methods for data science applications with practical focus.
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.
4.6
(89 ratings)
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What you'll learn
Practice integration techniques including integration by parts
Master numerical root-finding methods like bisection
Perform matrix diagonalization and understand SVD
Compute and apply partial derivatives in optimization
Skills you'll gain
This course includes:
1.8 Hours PreRecorded video
8 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course covers advanced mathematical concepts essential for data science applications. The curriculum includes integral calculus techniques, numerical analysis methods, matrix decomposition, and partial derivatives. Students learn practical applications through hands-on examples and quizzes, focusing on real-world data science scenarios rather than theoretical proofs.
Area Under The Curve
Module 1 · 1 Hours to complete
Numerical Analysis Intro
Module 2 · 25 Minutes to complete
Diagonalization & SVD
Module 3 · 52 Minutes to complete
Partial Derivatives & Steepest Descent
Module 4 · 50 Minutes to complete
Fee Structure
Instructors
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.
Instructor
Dr. James Bird is an Instructor at the University of Colorado Boulder, specializing in data science and applied mathematics. He holds a Ph.D. in Computer Science from the University of California, Santa Barbara, along with an M.S. in Statistics and an M.A. in Applied Physics/Applied Mathematics. His extensive academic background is complemented by a B.A. in Mathematics, providing him with a solid foundation in quantitative analysis.At CU Boulder, Dr. Bird teaches several courses that are integral to the data science curriculum, including "Essential Linear Algebra for Data Science," "Integral Calculus and Numerical Analysis for Data Science," and "Regression and Classification." His research interests focus on the implementation of artificial intelligence for deep space travel, reflecting his commitment to advancing knowledge in both theoretical and practical aspects of data science. Additionally, he has worked as a Statistician with Gallup since 2015, further enhancing his expertise in statistical methods and data analysis. Through his teaching and research, Dr. Bird plays a vital role in preparing students for successful careers in data science and analytics.
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4.6 course rating
89 ratings
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