Calculus for Machine Learning and Data Science
Completed by Ramya Rajagopal
May 23, 2026
26 hours (approximately)
Ramya Rajagopal'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: Machine Learning Algorithms
- Category: Applied Mathematics
- Category: Derivatives
- Category: Software Visualization
- Category: Machine Learning Methods
- Category: Applied Machine Learning
- Category: Calculus
- Category: Artificial Neural Networks
- Category: Deep Learning
- Category: Model Optimization
- Category: Numerical Analysis
