Support Vector Machine (SVM) Courses and Certifications

The Complete Machine Learning Course with Python

8044 ratings at Udemy

Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning & More!

• Udemy
• 17 hours 21 minutes
• Self-Paced
• Paid Course

Machine Learning & Deep Learning in Python & R

5988 ratings at Udemy

Covers Regression, Decision Trees, SVM, Neural Networks, CNN, Time Series Forecasting and more using both Python & R

• Udemy
• 1 day 9 hours 12 minutes
• Self-Paced
• Paid Course

Data Mining Methods

72 ratings at Coursera

Explore core data mining techniques including pattern analysis, classification, clustering, and outlier analysis. Learn advanced methods for complex data and discover research frontiers in the field.

• Coursera
• 1 day 25 minutes
• Self-Paced
• Paid Course

Complete Machine Learning with R Studio - ML for 2026

2725 ratings at Udemy

Linear & Logistic Regression, Decision Trees, XGBoost, SVM & other ML models in R programming language - R studio

• Udemy
• 12 hours 3 minutes
• Self-Paced
• Paid Course

Modern AI Models for Vision and Multimodal Understanding

29 ratings at Coursera

Explore cutting-edge AI architectures from SVMs and Fourier transforms to transformers, CLIP, and diffusion models for advanced vision and multimodal understanding applications.

• Coursera
• 12 hours 40 minutes
• Self-Paced
• Paid Course

Statistical Learning for Data Science

21 ratings at Coursera

Gain advanced statistical learning techniques for data science, including model selection, regression, classification, and unsupervised learning. Develop skills to explain and justify models effectively.

• Coursera
• 16 weeks, 9 hours/week
• Self-Paced
• Paid Course
• 3 courses

Machine Learning- From Basics to Advanced

2337 ratings at Udemy

A beginners guide to learn Machine Learning (including Hands-on projects - From Basic to Advance Level)

• Udemy
• 6 hours 49 minutes
• Self-Paced
• Paid Course

AI skills for Engineers: Supervised Machine Learning

8 ratings at edX

Learn the fundamentals of machine learning to help you correctly apply various classification and regression machine learning algorithms to real-life problems using the Python toolbox scikit-learn.

• edX
• 6 weeks, 6-8 hours/week
• Self-Paced
• Free Online Course (Audit)

Classification Analysis

Explore key classification algorithms, their applications, and evaluation methods. Gain hands-on experience through tutorials and case studies to solve real-world data analysis problems.

• Coursera
• 1 day 14 hours 14 minutes
• Self-Paced
• Paid Course

Trees, SVM and Unsupervised Learning

Explore support vector machines, neural networks, decision trees, and XG boost for predictive modeling. Learn data representation through PCA and clustering for practical applications in data science.

• Coursera
• 12 hours 59 minutes
• Self-Paced
• Paid Course

Machine Learning and AI: Support Vector Machines in Python

1926 ratings at Udemy

Artificial Intelligence and Data Science Algorithms in Python for Classification and Regression

• Udemy
• 8 hours 59 minutes
• Self-Paced
• Paid Course

Machine Learning and its Applications

47 ratings at Coursera

Master essential machine learning concepts and techniques through MATLAB, focusing on SVMs and ANNs for practical science and engineering applications, with hands-on experience in classification and regression.

• Coursera
• 16 hours 48 minutes
• Self-Paced
• Paid Course

The Supervised Machine Learning Bootcamp

1428 ratings at Udemy

Data Science, Python, sk learn, Decision Trees, Random Forests, KNNs, Ridge Lasso Regression, SVMs

• Udemy
• 5 hours 49 minutes
• Self-Paced
• Paid Course

Math for AI beginner part 1 Linear Algebra

33 ratings at Coursera

Explore essential linear algebra concepts for AI, including machine learning and deep learning algorithms, to build a strong foundation for understanding and applying AI techniques.

• Coursera
• 7 hours 1 minute
• Self-Paced
• Paid Course

Machine Learning: Concepts and Applications

25 ratings at Coursera

Comprehensive introduction to machine learning theory and practice using Python. Learn data preparation, modeling techniques, and evaluation methods with real-world datasets, focusing on practical applications and conceptual understanding.

• Coursera
• 1 day 13 hours 39 minutes
• Self-Paced
• Paid Course