Udemy – Hands-On Calculus with Python for Data Science & ML 2025-6

Hands-On Calculus with Python for Data Science & ML. This comprehensive course introduces fundamental calculus concepts and their practical application using the Python programming language to solve data science and machine learning problems. The course is designed to simultaneously enhance conceptual understanding and practical skills, and focuses directly on practical implementation without delving into purely abstract theories. The course’s audience, including students, developers, and data science enthusiasts, starts with the basics, such as functions and limits, and gradually progresses to derivatives, integrals, and multivariable calculus. Each mathematical concept is accompanied by Python coding examples and real-world applications, so participants can gain the analytical tools necessary to model complex problems, optimize algorithms, and better understand the mathematical foundations underlying machine learning methods. This interactive, project-based approach ensures not only mastery of mathematical fundamentals but also the ability to transform this knowledge into practical and implementable solutions.

What you will learn

• Core concepts of calculus: functions, limits, continuity, derivatives, integrals, optimization, and the principles of multivariable calculus are clearly explained with interactive Python examples.
• Python for Mathematics: In this course, participants will master libraries such as SymPy for symbolic mathematics, NumPy for numerical calculations, and Matplotlib for visual plotting of mathematical concepts.
• Solve practical problems: Using calculus, you solve real-world problems, from rates of change in physical systems to areas under curves and optimization challenges.
• Fundamentals for Machine Learning: You will understand how calculus underlies machine learning algorithms (gradients, cost functions, and optimization techniques), giving you a head start on machine learning development.
• Project-based learning: You build small projects like a derivative calculator, integral solver, and a simple gradient descent optimizer to solidify your understanding.
• Additional functionality: You’ll learn how to create and deploy an interactive web application using Shiny to showcase your Python math and computing projects, making your work accessible and impressive for presentations, portfolios, or teaching.

This course is suitable for people who:

• Students looking for a new, programming-based approach to calculus.
• Programmers and developers who want to sharpen their math skills for machine learning or data science.
• Anyone interested in learning how math and coding connect to solve real-world problems.