Calculus for Machine Learning and Data Science
Completed by NORAH EYAD ABDULAZIZ ALHINDI NORAH EYAD ABDULAZIZ ALHINDI
November 29, 2025
26 hours (approximately)
NORAH EYAD ABDULAZIZ ALHINDI NORAH EYAD ABDULAZIZ ALHINDI'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: Software Visualization
- Category: Machine Learning Methods
- Category: Derivatives
- Category: Machine Learning
- Category: Computer Programming
- Category: Calculus
- Category: Python Programming
- Category: Machine Learning Algorithms
- Category: Applied Machine Learning
- Category: Applied Mathematics
- Category: Advanced Mathematics
- Category: Model Optimization
