K-means Courses and Certifications

EDUCBA

R: Apply & Analyze K-Means Clustering for Unsupervised ML

Master K-Means clustering in R through hands-on implementation, data preparation, and customer segmentation analysis for real-world unsupervised machine learning applications.

• Coursera
• 2 hours 34 minutes
• On-Demand
• Paid Course

Embedding-Based Recommendation with Similarity Scoring

Master embedding-based music recommendations using vector transformations, cosine similarity, and clustering to build personalized suggestion systems.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

Microcredential

Mastering Clustering in Machine Learning with R

Unlock unsupervised learning in R through K-means, DBSCAN, and Hierarchical Clustering with data preprocessing and validation techniques for effective model performance assessment.

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

Unsupervised Learning and Clustering

Master unsupervised learning by building k-Means, mini-batch k-Means, PCA, and DBSCAN from scratch. Assess cluster quality using key metrics like homogeneity and completeness.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Stanford CS221 - Artificial Intelligence: Principles and Techniques - Autumn 2021

2 reviews

Master AI fundamentals through Stanford's comprehensive exploration of machine learning, search algorithms, probabilistic models, logic systems, and real-world applications.

• YouTube
• 1 day 7 hours 10 minutes
• On-Demand
• Free Video

Applied Unsupervised Learning in Python

Master unsupervised learning algorithms in Python to uncover hidden patterns, reduce dimensions, cluster data, model topics, and handle missing values using real-world datasets.

• Coursera
• 1 day 6 hours 13 minutes
• On-Demand
• Paid Course

Machine Learning with Python: k-Means Clustering

254 ratings at LinkedIn Learning

Learn the basics of k-means clustering, one of the most popular unsupervised machine learning approaches.

• LinkedIn Learning
• 51 minutes
• On-Demand
• Free Trial Available

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
• Paid Course

Machine Learning Algorithms with Python in Business Analytics

41 ratings at Coursera

Master machine learning algorithms in Python for business analytics, covering regression, classification, and clustering techniques to extract actionable insights from data.

• Coursera
• 16 hours 54 minutes
• On-Demand
• Paid Course

Coursera

Scikit-Learn For Machine Learning Classification Problems

19 ratings at Coursera

Learn to build and train classifier models using Scikit-Learn, exploring algorithms for classification, regression, and clustering, including support vector machines, random forests, and k-means.

• Coursera
• 1 hour 48 minutes
• On-Demand
• Paid Course

Foundations for Data Analytics Part 1

Discover Python fundamentals, data structures, and analytics techniques including clustering, time series analysis, and data wrangling for real-world applications.

• Coursera
• 16 hours 58 minutes
• On-Demand
• Paid Course

Machine Learning and Data Analytics Part 2

Explore advanced data mining techniques including clustering, neural networks, SVMs, and text mining with real-world applications across engineering sectors.

• Coursera
• 18 hours 7 minutes
• On-Demand
• Paid Course

Coursera

Scikit-Learn to Solve Regression Machine Learning Problems

Learn to build and train regression models using Scikit-Learn, exploring algorithms like support vector machines, random forests, and gradient boosting. Gain practical skills applicable to various industries.

• Coursera
• 1 hour 56 minutes
• On-Demand
• Paid Course

EDUCBA

Advanced Machine Learning with R: Apply & Predict

Master advanced ML techniques in R: clustering, Naive Bayes, neural networks, time series forecasting, PCA, gradient boosting, and market basket analysis for production-ready models.

• Coursera
• 17 hours 40 minutes
• On-Demand
• Paid Course

EDUCBA

Machine Learning with Python: Case Studies

Master machine learning through hands-on Python case studies covering regression, clustering, classification, and feature engineering with real-world datasets like salary prediction and credit risk.

• Coursera
• 8 hours 57 minutes
• On-Demand
• Paid Course