Machine Learning with Python
Completed by Chris Antonopoulou
January 16, 2026
20 hours (approximately)
Chris Antonopoulou'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: Model Evaluation
- Category: Model Optimization
- Category: Statistical Methods
- Category: Predictive Modeling
- Category: Machine Learning Algorithms
- Category: Logistic Regression
- Category: Supervised Learning
- Category: Applied Machine Learning
- Category: Dimensionality Reduction
- Category: Machine Learning Methods
- Category: Python Programming
- Category: Classification Algorithms
