- Unsupervised Learning
- Feature Engineering
- Regression Analysis
- Machine Learning
- Python Programming
- Classification Algorithms
- Predictive Modeling
- Scikit Learn (Machine Learning Library)
- Applied Machine Learning
- Model Evaluation
- Logistic Regression
- Dimensionality Reduction
Machine Learning with Python
Completed by Mohamed Morad
May 15, 2024
20 hours (approximately)
Mohamed Morad'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
