Machine Learning with Python: Build Real-World ML Models
Completed by Daniel Fonseca
February 10, 2026
20 hours (approximately)
Daniel Fonseca's account is verified. Coursera certifies their successful completion of Machine Learning with Python: Build Real-World ML Models
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: Machine Learning Methods
- Category: Supervised Learning
- Category: Machine Learning Algorithms
- Category: Logistic Regression
- Category: Applied Machine Learning
- Category: Python Programming
- Category: Model Evaluation
- Category: Model Optimization
- Category: Machine Learning
- Category: Dimensionality Reduction
- Category: Regression Analysis
- Category: Unsupervised Learning
