Probability & Statistics for Machine Learning & Data Science
Completed by Abdullah Hossam Siam
February 1, 2026
33 hours (approximately)
Abdullah Hossam Siam's account is verified. Coursera certifies their successful completion of Probability & Statistics for Machine Learning & Data Science
What you will learn
Describe and quantify the uncertainty inherent in predictions made by machine learning models
Visually and intuitively understand the properties of commonly used probability distributions in machine learning and data science
Apply common statistical methods like maximum likelihood estimation (MLE) and maximum a priori estimation (MAP) to machine learning problems
Assess the performance of machine learning models using interval estimates and margin of errors
Skills you will gain
- Category: Statistical Machine Learning
- Category: A/B Testing
- Category: Sampling (Statistics)
- Category: Statistical Methods
- Category: Probability Distribution
- Category: Exploratory Data Analysis
- Category: Statistical Visualization
- Category: Probability
- Category: Bayesian Statistics
- Category: Statistics
- Category: Statistical Hypothesis Testing
- Category: Statistical Inference
