- Classification And Regression Tree (CART)
- Regression Analysis
- Applied Machine Learning
- Machine Learning
- Supervised Learning
- Scikit Learn (Machine Learning Library)
- Unsupervised Learning
- Dimensionality Reduction
- Predictive Modeling
- Feature Engineering
- Decision Tree Learning
- Statistical Modeling
Machine Learning with Python
Completed by Oriol Rius Vilaseca
May 3, 2025
20 hours (approximately)
Oriol Rius Vilaseca'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
