DBSCAN Courses and Certifications

Intro to Unsupervised Machine Learning

Master unsupervised machine learning through hands-on practice with clustering, dimensionality reduction, and advanced algorithms using the Iris dataset for practical data analysis applications.

• CodeSignal
• On-Demand
• Free Certificate

Unsupervised Learning and Clustering

Master unsupervised learning algorithms from scratch, including k-Means, PCA, and DBSCAN. Build clustering implementations, visualize results, and evaluate performance using essential metrics.

• CodeSignal
• On-Demand
• Free Certificate

Density-Based Clustering Simplified

Master density-based clustering through DBSCAN algorithm implementation, from basic concepts to advanced parameter tuning, with hands-on Python examples using scikit-learn.

• CodeSignal
• On-Demand
• Free Certificate

Cluster Performance Unveiled

Master advanced clustering validation techniques using Silhouette Score, Davies-Bouldin Index, and Cross-Tabulation Analysis to optimize algorithm performance and identify ideal cluster structures.

• CodeSignal
• On-Demand
• Free Certificate

Microcredential

Mastering Clustering in Machine Learning

Master clustering algorithms and validation techniques for unsupervised machine learning, from K-means and DBSCAN to hierarchical methods and performance metrics.

• CodeSignal
• On-Demand
• Free Certificate
• 4 courses

Advanced Methods in Machine Learning Applications

Master advanced machine learning techniques for complex problem-solving. Explore ensemble learning, regression analysis, unsupervised learning, and reinforcement learning. Gain practical skills to implement and optimize sophisticated models.

• Coursera
• 19 hours 58 minutes
• On-Demand
• Free Online Course (Audit)

Data Science Foundations: Data Mining

304 ratings at LinkedIn Learning

Learn the key concepts and skills behind one of the most important elements of data science: data mining.

• LinkedIn Learning
• 3 hours 3 minutes
• On-Demand
• Free Trial Available

Great Learning

Customer Segmentation Using Clustering

Learn customer segmentation using four clustering techniques: KMeans, DBSCAN, MeanShift, and Agglomerative. Apply these methods to real-world data and compare their effectiveness in dividing customers into meaningful groups.

• YouTube
• 58 minutes
• On-Demand
• Free Video

Applied Algebraic Topology Network

Practical Clustering and Topological Data Analysis

Explore clustering algorithms and topological data analysis from a data science perspective, covering techniques from k-means to DBSCAN and dimensionality reduction methods like UMAP.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

Data Science Dojo

Approaches to Fraud Detection - Autoencoder and Isolation Forest - Fraud Detection Using ML

Learn fraud detection techniques using KNIME, including random forest, autoencoder, and isolation forest. Explore methods for both labeled and unlabeled data, with practical demonstrations and insights on implementation.

• YouTube
• 53 minutes
• On-Demand
• Free Video

UofU Data Science

Distance Metric Learning and Outlier Detection in Data Mining - Spring 2023

Delve into advanced data mining concepts, focusing on distance metric learning, outlier detection techniques, and practical applications of DBSCAN for effective data analysis.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video

UofU Data Science

Visualization for Data Science - Filtering, Aggregation, and Clustering

Master data visualization techniques through filtering, aggregation, and interactive queries, exploring real-world applications like gerrymandering analysis and clustering methods including K-means and DBScan.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

Conf42

Unveiling Clustering in BERTopic Topic Modeling

Explore BERTopic clustering for topic modeling, covering HDBSCAN algorithm, density-based spatial clustering, and performance comparisons. Gain insights into advanced text analysis techniques.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Southwestern University of Finance and Economics

机器学习

Dive into 机器学习的理论与实践，掌握从线性模型到集成学习的核心算法，通过实践案例培养独立思考能力，并在专业团队指导下探索人工智能应用。

• XuetangX
• On-Demand
• Free Online Course

Clustering Geolocation Data Intelligently in Python

401 ratings at Coursera

Learn to clean, preprocess, and cluster geolocation data using K-Means, DBSCAN, and HDBSCAN algorithms. Visualize results interactively and evaluate model performance for improved spatial analysis.

• Coursera
• 1 hour 55 minutes
• Finished
• Paid Course