Math 0-1: Calculus for Data Science & Machine Learning Course

A Casual Guide for Artificial Intelligence, Deep Learning, and Python Programmers

This course will cover Calculus 1 (limits, derivatives, and the most important derivative rules), Calculus 2 (integration), and Calculus 3 (vector calculus). It will even include machine learning-focused material you wouldn’t normally see in a regular college course. We will even demonstrate many of the concepts in this course using the Python programming language (don’t worry, you don’t need to know Python for this course). In other words, instead of the dry old college version of calculus, this course takes just the most practical and impactful topics and provides you with skills directly applicable to machine learning and data science, so you can start applying them today.

Best Seller Course: Linear Algebra for Data Science & Machine Learning A-Z 2023

What you’ll learn

• Limits, limit definition of derivative, derivatives from first principles
• Derivative rules (chain rule, product rule, quotient rule, implicit differentiation)
• Integration, area under curve, fundamental theorem of calculus
• Vector calculus, partial derivatives, gradient, Jacobian, Hessian, steepest ascent
• Optimize (maximize or minimize) a function
• l’Hopital’s Rule
• Newton’s Method

Recommended Course: Precalculus 2: Polynomials and rational functions

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