Robotics

STANFORD — This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). [coursera]

IBM — In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. [coursera]

VANDERBILT — Learn how to apply prompt engineering to effectively work with large language models, like ChatGPT; how to use prompt patterns to tap into powerful capabilities within large language models; and how to create complex prompt-based applications for your life, business, or education. [coursera]

U BUFFALO — By the end of this course, learners will understand what computer vision is, as well as its mission of making computers see and interpret the world as humans do, by learning core concepts of the field and receiving an introduction to human vision capabilities. They are equipped to identify some key application areas of computer vision and understand the digital imaging process. The course covers crucial elements that enable computer vision: digital signal processing, neuroscience and artificial intelligence. [coursera]

COLUMBIA — Master the working principles of a digital camera and learn the fundamentals of imaging processing; Create a theory of feature detection and develop algorithms for extracting features from images; Explore novel methods for using visual cues (shading, defocus, etc.) to recover the 3D shape of an object from multiple images or viewpoints; Get exposed to fundamental perceptions tasks such as image segmentation, object tracking, and object recognition. [coursera]

STANFORD – Break into AI with Machine Learning. Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, three-course program by AI visionary Andrew Ng. [coursera]

HARVARD — Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques. [edX]