The Math of Data Science: Linear Algebra– edX
Linear algebra is at the core of all of ultramodern mathematics, and is used far and wide from statistics and data wisdom, to economics, drugs and electrical engineering. still, learning the subject isn't basically about acquiring computational capability, but is more a matter of ignorance in its language and proposition.
In this course, you start with systems of direct equations and connect them to vectors and vector spaces, matrices, and direct transformations. They emphasize vocabulary throughout, so that scholars feel comfortable working with different aspects. They also introduced matrix and vector operations similar to matrix addition and subtraction, paying particular attention to their original purpose. Scholars not only learn how to compute, but also why they work the way they do.
They discuss important generalizations of bases and dimensions, which form the basis for many more advanced generalizations of direct algebra. The final chapter deals with the inner products, allowing us to use algebra directly to access the results; you'll see how this enables operations ranging from statistics and direct retrieval to digital audio.
At a glance
- Institution: RICEx
- Subject: Math
- Level: Intermediate
- Prerequisites:High school algebra. Some calculus is useful for certain examples or problems but is not strictly necessary.
- Language: English
- Video Transcript: English
- Associated programs:
- MicroBachelors Program in Elements of Data Science
What you'll learn
- The relationships between linear equations, matrices, and linear transformations; the principles of vector and matrix operations; the significance of basis and dimension of a vector space; the applications of inner products and orthogonality.
Time to Complete- 8 Weeks( If you spend 6-8 hours per week)
Rating: 4.0/5.0
Enroll here: edx.org/course/math-of-data-science-linear-algebra
