Machine Learning with Python
Completed by Shalom Friss
March 9, 2026
20 hours (approximately)
Shalom Friss's account is verified. Coursera certifies their successful completion of Machine Learning with Python
What you will learn
Explain key concepts, tools, and roles involved in machine learning, including supervised and unsupervised learning techniques.
Apply core machine learning algorithms such as regression, classification, clustering, and dimensionality reduction using Python and scikit-learn.
Evaluate model performance using appropriate metrics, validation strategies, and optimization techniques.
Build and assess end-to-end machine learning solutions on real-world datasets through hands-on labs, projects, and practical evaluations.
Skills you will gain
- Category: Statistical Methods
- Category: Predictive Modeling
- Category: Model Evaluation
- Category: Model Optimization
- Category: Machine Learning
- Category: Machine Learning Algorithms
- Category: Unsupervised Learning
- Category: Logistic Regression
- Category: Supervised Learning
- Category: Python Programming
- Category: Classification Algorithms
- Category: Scikit Learn (Machine Learning Library)
