Calculus for Machine Learning and Data Science
Completed by Samuel Gonzalez
January 23, 2026
26 hours (approximately)
Samuel Gonzalez'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: Python Programming
- Category: Software Visualization
- Category: Machine Learning Methods
- Category: Applied Mathematics
- Category: Applied Machine Learning
- Category: Machine Learning Algorithms
- Category: Calculus
- Category: Deep Learning
- Category: Model Optimization
- Category: Artificial Neural Networks
- Category: Computer Programming
- Category: Machine Learning
