Calculus for Beginners - Calculus for Machine Learning

This course introduces core calculus concepts through limits, continuity, derivatives, differentiation techniques, optimization, Newton’s method, and antiderivatives. It is intended for beginners seeking a thorough foundation, including learners interested in machine learning.

Syllabus

) A Preview of Calculus.
) The Limit of a Function. .
) The Limit Laws.
) Continuity.
) The Precise Definition of a Limit.
) Defining the Derivative.
) The Derivative as a Function.
) Differentiation Rules.
) Derivatives as Rates of Change.
) Derivatives of Trigonometric Functions.
) The Chain Rule.
) Derivatives of Inverse Functions.
) Implicit Differentiation.
) Derivatives of Exponential and Logarithmic Functions.
) Partial Derivatives.
) Related Rates.
) Linear Approximations and Differentials.
) Maxima and Minima.
) The Mean Value Theorem.
) Derivatives and the Shape of a Graph.
) Limits at Infinity and Asymptotes.
) Applied Optimization Problems.
) L'Hopital's Rule.
) Newton's Method.
) Antiderivatives.