Calculus for Machine Learning and Data Science
Completed by Matthew Bevivino
October 9, 2025
26 hours (approximately)
Matthew Bevivino's account is verified. Coursera certifies their successful completion of Calculus for Machine Learning and Data Science
What you will learn
Analytically optimize different types of functions commonly used in machine learning using properties of derivatives and gradients
Approximately optimize different types of functions commonly used in machine learning
Visually interpret differentiation of different types of functions commonly used in machine learning
Perform gradient descent in neural networks with different activation and cost functions
Skills you will gain
- Category: Numerical Analysis
- Category: Model Optimization
- Category: Artificial Neural Networks
- Category: Deep Learning
- Category: Calculus
- Category: Applied Machine Learning
- Category: Machine Learning Algorithms
- Category: Python Programming
- Category: Software Visualization
- Category: Machine Learning Methods
- Category: Applied Mathematics
- Category: Derivatives
