- Python Programming
- Feature Engineering
- Predictive Modeling
- Scikit Learn (Machine Learning Library)
- Applied Machine Learning
- Dimensionality Reduction
- Logistic Regression
- Unsupervised Learning
- Model Evaluation
- Supervised Learning
- Decision Tree Learning
- Regression Analysis
Machine Learning with Python
Completed by SEBASTIAN FREIDANK
October 23, 2020
20 hours (approximately)
SEBASTIAN FREIDANK'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
