- Specialization:ÌýClimate Change Anomalies
- Instructor:ÌýOsita Onyejekwe
- Prior knowledge needed:ÌýIntro to R programming
Learning Outcomes
- Analyze and differentiate between various machine learning algorithms, including unsupervised and supervised methods Ìý
- Apply dimensionality reduction techniques, such as Principal Component Analysis (PCA) and Singular Value Decomposition (SVD), to complex datasets
- Implement supervised learning algorithms using Python, and evaluate their performance through practical exercises and real-world case studies.
- Develop and apply effective clustering methods to analyze and segment data Ìý
Course Content
Note: This page is periodically updated. Course information on the Coursera platform supersedes the information on this page. Click View on Coursera buttonÌýabove for the most up-to-date information.