Supervised Learning Courses and Certifications

Packt

Data Science - Supervised Machine Learning in Python

Apply supervised machine learning theory in Python through hands-on work with real datasets, model tuning, and deployment as web services.

• Coursera
• 8 weeks, 1 hour a week
• 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 a week
• Self-Paced
• Free Online Course (Audit)

Supervised Learning

Learn how to build supervised learning models using Python and Sklearn (Sci-Learn). This course includes the most popular supervised learning models, including K-Nearest Neighbor (KNN), Support Vector

• edX
• 6 weeks, 5-7 hours a week
• Self-Paced
• Free Online Course (Audit)

Learning from Input and Output: Supervised Learning: Wolfram U Class

Build supervised learning models in Wolfram Language: classify data with Classify, predict values with Predict, set options like Methods and PerformanceGoal, and compute Accuracy and ConfusionMatrix.

• Wolfram U
• 40 minutes
• Self-Paced
• Free Online Course

Data Science Courses

Supervised Learning - STAT 841 Fall 2017

Master supervised learning fundamentals including LDA, PCA, neural networks, SVMs, and CNNs through comprehensive statistical machine learning theory and applications.

• YouTube
• 17 hours 33 minutes
• Self-Paced
• Free Video

Machine Learning: Regression

20 ratings

Build regression models to predict house prices in Python: fit simple and multiple linear regression, ridge and lasso, nearest neighbor and kernel regression.

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

Machine Learning in the Tidyverse

119 ratings at DataCamp

Build, tune, and evaluate regression and classification models in R using the List Column Workflow, with broom, tidyr, and purrr to manage many models at once.

• DataCamp
• 5 hours
• Self-Paced
• Free Trial Available

Machine Learning with caret in R

45 ratings at DataCamp

Machine learning is the study and application of algorithms that learn from and make predictions on data.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Machine Learning with scikit-learn

14 ratings at DataCamp

Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Great Learning

Supervised Learning Full Course - Supervised Learning Tutorial for Beginners

In this video we will be explaining various advantages in detail. We will also be covering different topics such as, What is Machine Learning, What are their types, Python implementation for Regression, and much more.

• YouTube
• 4 hours 46 minutes
• Self-Paced
• Free Video

Great Learning

Supervised Learning Projects Tutorial - Machine Learning Tutorial

Practice supervised learning through projects involving COVID-19 prediction, credit card fraud and default detection, and Pokémon data analysis.

• YouTube
• 2 hours 59 minutes
• Self-Paced
• Free Video

Paul Hand

Supervised Machine Learning Review

Review supervised learning through loss functions, bias-variance tradeoffs, and the surprising double-descent behavior of highly overparameterized neural networks.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

UofU Data Science

Supervised Learning: The Setup and Hypothesis Spaces - Lecture 2

Dive into supervised learning fundamentals through interactive examples, exploring instance spaces, label spaces, and hypothesis spaces while understanding their crucial roles in machine learning.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

UofU Data Science

Supervised Learning: Instance Space, Label Space, and Hypothesis Space - Lecture 2

Dive into supervised learning fundamentals through interactive examples, exploring instance spaces, label spaces, and hypothesis spaces while understanding their crucial roles in machine learning.

• YouTube
• 1 hour 17 minutes
• Self-Paced
• Free Video

Foundational Machine Learning Models with Sklearn

Build linear regression, logistic regression, and decision tree models in Sklearn on the Iris dataset, then evaluate with accuracy, MAE and confusion matrices and tune hyperparameters.

• CodeSignal
• 4 hours
• Self-Paced
• Free Certificate