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 [...]

For students who already grasp the fundamentals of machine learning and wish to enhance their capacity to create more dependable and accurate models, Kaggle’s Intermediate Machine Learning is a useful, hands-on course. Essential real-world machine learning techniques are covered in the course, including how to deal with missing data, work [...]

Kaggle’s Introduction to Machine Learning is a hands-on, beginner-friendly micro-course that uses scikit-learn and Python to present the basic ideas of machine learning. Students will construct their first machine learning models, investigate and comprehend datasets, verify model performance, deal with overfitting and underfitting, and use methods like random forests and [...]

Google created the free, beginner-friendly Machine Learning Crash Course (MLCC) to teach the principles of contemporary AI and machine learning. Easy-to-understand lectures, Google expert videos, interactive visualizations, tests, and practical coding tasks are all included in this course. Large language models (LLMs), neural networks, embeddings, linear regression, classification, data preparation, [...]

Duke University offers an intermediate-level course on Coursera called Introduction to Machine Learning. With subjects including logistic regression, neural networks, deep learning, computer vision, natural language processing (NLP), and reinforcement learning, the course offers a solid foundation in machine learning ideas. Through practical exercises with Python and PyTorch, students learn [...]

Andrew Ng teaches a beginner-friendly AI course called Machine Learning Specialization, which is provided via Stanford Online and DeepLearning.AI. Supervised learning, unsupervised learning, neural networks, decision trees, recommender systems, and best practices for creating practical AI applications are all covered in this course, which offers a hands-on introduction to machine [...]

Andrew Ng’s machine learning specialty is DeepLearning.AI, and Stanford Online is an industry-recognized, beginner-friendly curriculum created to establish a solid foundation in AI and machine learning. Neural networks, decision trees, recommender systems, supervised learning, unsupervised learning, and machine learning best practices are all covered in this area. Students get practical [...]