What you’ll learn:
- Master the foundations of unsupervised Machine Learning in Python, including clustering, anomaly detection, dimensionality reduction, and recommenders
- Prepare data for modeling by applying feature engineering, selection, and scaling
- Fit, tune, and interpret three types of clustering algorithms: K-Means Clustering, Hierarchical Clustering, and DBSCAN
- Use unsupervised learning techniques like Isolation Forests and DBSCAN for anomaly detection
- Apply and interpret two types of dimensionality reduction models: Principal Component Analysis (PCA) and t-SNE
- Build recommendation engines using content-based and collaborative filtering techniques, including Cosine Similarity and Singular Value Decomposition (SVD)
Maven Analytics is the first purpose-built, online platform for data analysts to learn new skills, showcase their work, and connect with peers and employers.
Named one of the top 10 education companies revolutionizing the industry, Maven’s award-winning Guided Learning model allows users to create personalized learning plans, build public portfolios, connect with expert instructors and career coaches, and join a community of world-class analytics talent.
We’ve helped 1,000,000+ students build job-ready skills, master tools like Excel, SQL, Power BI, Tableau and Python, and build the foundation for a successful career.