Johns Hopkins University’s practical machine learning course teaches students how to create and assess machine learning prediction models using actual data. Training and test datasets, cross-validation, overfitting, feature engineering, preprocessing, and machine learning techniques including regression, classification trees, Naive Bayes, and random forests are all covered in the course. Additionally, [...]

The University of London’s Machine Learning for All is a beginner-friendly course that introduces students to the basic ideas of artificial intelligence (AI) and machine learning without having any prior knowledge of mathematics or programming. Students investigate how machines learn from data, comprehend how data affects AI systems, look at [...]

Simplilearn’s Machine Learning Basics (Machine Learning using Python) is a free online course that introduces students to the principles of artificial intelligence and machine learning. Important topics covered in the course include supervised and unsupervised learning, logistic and linear regression, K-Means clustering, Support Vector Machines (SVM), Naive Bayes, time series [...]

The fundamental ideas of machine learning are introduced in Great Learning’s beginner-friendly online course, Introduction to Machine Learning. Supervised and unsupervised learning, linear regression, classification, recommendation systems, machine learning processes, and real-world case studies are all covered in the course. Additionally, it helps students develop a solid foundation in AI [...]

The goal of the beginner-friendly course AWS Machine Learning Foundations is to acquaint students with the principles of machine learning and its practical uses with AWS technology. Supervised and unsupervised learning, model creation, computer vision, reinforcement learning, and generative AI are among the key machine learning principles covered in the [...]

Harvard University’s intermediate-level course CS50, Introduction to Artificial Intelligence with Python, exposes students to the basic ideas and techniques behind contemporary artificial intelligence. Students investigate subjects including graph search algorithms, knowledge representation, probability, machine learning, neural networks, reinforcement learning, and natural language processing through practical Python projects. The course aids [...]

The goal of the free, beginner-friendly online course Elements of AI is to teach non-experts the principles of artificial intelligence (AI). The course, which was developed by the University of Helsinki and MinnaLearn, uses hands-on activities and simple instruction to cover important AI concepts like machine learning, neural networks, AI [...]

Andrew Ng, the inventor of DeepLearning, wrote AI For Everyone, a non-technical, beginner-friendly introduction to artificial intelligence. AI and a co-founder of Coursera. The course aids students in comprehending basic AI principles, machine learning jargon, AI project workflows, business applications of AI, and the impact of AI on society. It [...]

DeepLearning offers a beginner-friendly course called Supervised Machine Learning: Regression and Classification.AI at Stanford University, where renowned AI specialist Andrew Ng teaches the first course of the Machine Learning Specialization. By teaching students how to create predictive models using Python, NumPy, and scikit-learn, it offers a solid foundation in machine [...]

IBM’s interactive intermediate-level course Machine Learning with Python teaches students how to create, train, and assess machine learning models using Python and Scikit-learn. Important topics covered in the course include model evaluation, regression, classification, clustering, dimensionality reduction, supervised and unsupervised learning, and optimization approaches. Learners acquire experience creating end-to-end machine [...]