Calculus for Machine Learning and Data Science
Completed by Tatiana Torres Díaz
January 10, 2026
26 hours (approximately)
Tatiana Torres Díaz'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: Deep Learning
- Category: Artificial Neural Networks
- Category: Applied Machine Learning
- Category: Model Optimization
- Category: Machine Learning
- Category: Computer Programming
- Category: Derivatives
- Category: Applied Mathematics
- Category: Python Programming
- Category: Machine Learning Software
- Category: Machine Learning Methods
