Machine Learning with Python
Completed by Jhon Yam Borges
January 31, 2026
20 hours (approximately)
Jhon Yam Borges'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: Unsupervised Learning
- Category: Logistic Regression
- Category: Model Evaluation
- Category: Model Optimization
- Category: Machine Learning
- Category: Statistical Methods
- Category: Python Programming
- Category: Predictive Modeling
- Category: Model Training
- Category: Supervised Learning
- Category: Classification Algorithms
- Category: Applied Machine Learning
