Linear functions change at a constant rate, and that in turn, makes the rate of change of a linear function a constant. This and other related insights into linear and other mathematical functions can be quantified using calculus. Through this course, you'll examine the steps involved in applying the differentiation operation to study a moving particle. You'll then understand how the partial derivative of a function that depends on multiple independent variables is computed with respect to one of those independent variables by holding all other independent variables constant. This course will also allow you to investigate how partial derivatives play a crucial role in the training phase of building a machine learning (ML) model. Upon completion of this course, you will be able to compute the partial derivative of a function that depends on multiple independent variables and better understand the training process of a machine learning model.

Calculus is a branch of mathematics that deals with continuous change and with how the output of a function changes when the inputs into that function change by vanishingly small amounts. Calculus has wide-ranging applications - in optimization, machine learning, economics, and medicine. You will start this course by defining a derivative in terms of its mathematical formula and interpreting that derivative of a function at a point in two ways: as the slope of the tangent line to the function at that point or as the instantaneous rate of change of that function at that point. You will also apply these concepts to a constant function, verify that its derivative is zero, and understand the reason behind it. By the time you finish this course, you'll have a good foundation in the basics of differential calculus.

Integral calculus is a major branch of calculus that deals with integrating - i.e., aggregating - an infinite number of infinitesimal increments to a function. Integration is the inverse operation of differentiation and has wide-ranging applications across science, engineering, and social sciences. Begin this course by understanding how integration can be used to compute the area under a curve. You'll then explore the relationship between derivatives and integrals and discover how differentiation and integration are inverse operations. You'll wrap up the course by investigating the steps involved in computing the integral of several different types of functions and visualize these integrals using a combination of SymPy, Seaborn, and Matplotlib. By the time you finish this course, you'll be able to solve definite as well as indefinite integrals and visualize such integrals as the area under a curve in Python.