Supervised Learning Courses and Certifications

Predicting Extreme Climate Behavior with Machine Learning

Apply machine learning to climate datasets: reduce dimensions with PCA/SVD, cluster with K-Means and hierarchical methods, and classify using logistic regression, decision trees, SVMs, and neural networks.

• Coursera
• 5 weeks, 5 hours a week
• Self-Paced
• Paid Course

Coursera

Support Vector Machines in Python, From Start to Finish

162 ratings at Coursera

Build a support vector machine classifier in Python with scikit-learn and an RBF kernel to predict heart disease from UCI Machine Learning Repository data.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

Machine Learning and AI: Support Vector Machines in Python

1933 ratings at Udemy

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

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

EDUCBA Career Certificate

Applied Python: Web Dev, Machine Learning & Cryptography

75 ratings at Coursera

Build and deploy Python web applications, then apply linear regression, sentiment analysis, and cryptography in project-based case studies.

• Coursera
• 4 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 5 courses

Coursera

Mining Quality Prediction Using Machine & Deep Learning

70 ratings at Coursera

Predict silica content in iron ore concentrate: train linear regression, decision tree, random forest, gradient boosting and neural network models in Python and compare MSE, RMSE, R2.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

Predictive Modeling with Logistic Regression using SAS

63 ratings at Coursera

Model individual behavior with SAS PROC LOGISTIC: fit and score logistic models, recode categorical predictors, handle missing values and multicollinearity, and compare model performance.

• Coursera
• 6 weeks, 3 hours a week
• Self-Paced
• Paid Course

Coursera

Breast Cancer Prediction Using Machine Learning

57 ratings at Coursera

Build a logistic regression classifier with Scikit-learn in Google Colab to classify Breast Cancer Wisconsin data as malignant or benign, cleaning and preparing the data first.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

EDUCBA Career Certificate

Python for Data Science: Real Projects & Analytics

47 ratings at Coursera

Analyze and visualize datasets in Python, apply statistical methods, optimize advanced code, build logistic regression models, and forecast sales with time series.

• Coursera
• 4 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 5 courses

Logistic Regression using SAS - Indepth Predictive Modeling

1147 ratings at Udemy

Analytics /Machine Learning / Data Science: Statistical / Econometrics foundation, SAS Program details, Modeling demo

• Udemy
• 17 hours 57 minutes
• Self-Paced
• Paid Course

Coursera

Naive Bayes 101: Resume Selection with Machine Learning

17 ratings at Coursera

Build a Naïve Bayes classifier that predicts whether a resume text is flagged, training on a labeled set of 125 resumes for automated screening.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

Fractal Analytics

Foundations of Machine Learning

14 ratings at Coursera

Build and evaluate machine learning models: prepare data with EDA and feature engineering, train KNN, linear and logistic regression, decision trees, and KMeans and DBSCAN clustering.

• Coursera
• 6 weeks, 4 hours a week
• Self-Paced
• Paid Course

EDUCBA

SPSS: Apply & Interpret Logistic Regression Models

13 ratings at Coursera

Build and interpret logistic regression models in IBM SPSS: configure variables, read output tables, and assess prediction accuracy through heart pulse and smoking behavior case studies.

• Coursera
• 2 weeks, 2 hours a week
• Self-Paced
• Paid Course

Coursera

Scikit-Learn to Solve Regression Machine Learning Problems

11 ratings at Coursera

Build and train regression models with Scikit-Learn in a hands-on Python project you can add to a portfolio.

• Coursera
• 1 hour 56 minutes
• Self-Paced
• Paid Course

Machine Learning Algorithms

Learn four core machine learning algorithms — naïve Bayes, support vector machines, decision trees, and clustering — and how each one classifies or groups data.

• Coursera
• 4 weeks, 4 hours a week
• Self-Paced
• Paid Course

Statistical Learning

Learn statistical learning in Python: linear regression with ridge and LASSO, LDA and logistic classification, splines, kernel smoothing, model selection, maximum likelihood, SVMs and neural networks.

• Coursera
• 9 weeks, 13 hours a week
• Self-Paced
• Paid Course