Although lay individuals might use machine learning as being synonymous with artificial intelligence, the academic world treats them as two distinct but related areas. The emphasis shifts enormously between the two. According to Carnegie Mellon University, “Machine learning is dedicated to furthering the scientific understanding of automated learning, and to producing the next generation of tools for data analysis and decision making based on that understanding”.

The Department of Computer Science at the University College of London offers an MSc in Machine Learning as “a unique programme that introduces students to the computational, mathematical and business views of machine learning. The programme is led and taught by world renowned researchers from the Department of Computer Science and the Gatsby Computational Neuroscience Unit” ((http://www.cs.ucl.ac.uk/degrees/msc_ml/).

The University of Cambridge offers an MPhil in Machine Learning, Speech and Language Technology, “taught from within our Information Engineering Division”. “The course aims: to teach the state of the art in machine learning, speech and language processing; to give students the skills and expertise necessary to take leading roles in industry; to equip students with the research skills necessary for doctoral study” (http://www.graduate.study.cam.ac.uk/courses/directory/egegmpmsl). The University of Bristol offers an MSc Advanced Computing – Machine Learning, Data Mining and High-Performance Computing which is “concerned with the automated analysis of large-scale data by computer, in order to extract the useful knowledge hidden in it. Using state-of-the-art Artificial Intelligence methods, this technology builds computer systems capable of learning from past experience, allowing them to adapt to new tasks, predict future developments, and provide intelligent decision support” (http://www.bristol.ac.uk/study/postgraduate/2016/eng/msc-adv-computing-machine-learning/).

The KTH Royal Institute of Technology, Stockholm, offers an MSc Machine Learning. According to them, “Machine Learning is a scientific discipline focused on the development of algorithms that spot patterns or make predictions from empirical data” (http://www.mastersportal.eu/studies/14874/machine-learning.html).

The MS in Machine Learning at Carnegie Mellon is part of CMU’s Machine Learning Department, which is made up of a multi-disciplinary team of faculty and students across several academic departments. (https://www.ml.cmu.edu/prospective-students/ms-in-machine-learning.html). Columbia University’s “Machine Learning Track is intended for students who wish to develop their knowledge of machine learning techniques and applications. Machine learning is a rapidly expanding field with many applications in diverse areas such as bioinformatics, fraud detection, intelligent systems, perception, finance, information retrieval, and other areas” (http://www.cs.columbia.edu/education/ms/machineLearning). The Ohio State University offers a Masters in Applied Computer Engineering. In their own words, “Applied Machine Learning utilizes a variety of learning mechanisms for particular tasks; many of our research groups use machine learning to accomplish tasks in speech and language processing, computer vision, and data mining. While algorithmic development is a part of the process, significant effort is spent in developing task-specific representations for machine learning processes, particularly utilizing cognitive, physiological, or perceptual constraints in design” (https://cse.osu.edu/research/applied-machine-learning). Students should take a look at New York University’s several courses (http://cs.nyu.edu/home/courses/) offered through its Department of Computer Science.