Learn Mathematical Foundations for Data Science. Review key concepts in algebra, calculus, linear algebra, and numerical analysis that are critical for Data Science.

What you'll learn
Compute simple derivatives.
Convert between linear systems and matrix notation and use matrix algebra to solve linear systems.
Factor a simple matrix using Singular Value Decomposition (SVD).
Skills you'll gain
Integrals
Matrix Algebra
Diagonalization
Numerical Analysis
Derrivatives
Data Science is growing rapidly, creating opportunities for careers across a variety of fields. This specialization is designed for learners embarking on careers in Data Science. Learners are provided with a concise overview of the foundational mathematics that are critical in Data Science. Topics include algebra, calculus, linear algebra, and some pertinent numerical analysis. Expressway to Data Science is also an excellent primer for students preparing to complete CU Boulder's Master of Science in Data Science program.
This specialization is designed to prepare learners to successfully complete Statistical Modeling for Data Science Application, which is part of CU Boulder's Master of Science in Data Science (MS-DS) program.
Applied Learning Project
Learners will complete quizzes in each of the courses in order to test their understanding of the content as they progress. This specialization does not include any projects or final exams as it is meant to be a fast-paced content review to prepare learners for the higher-level maths required in Data Science.

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