Best Universities for Masters certificate program in Artificial Intelligence and Machine Learning

The Graduate Certificate in Statistics and Machine Learning is designed to formalize the training of students who contribute to or make use of statistics and machine learning as a significant part of their research. In addition, it serves to recognize the accomplishments of graduate students across the University who go beyond the requirements of their own degree programs to acquire additional training in statistics and machine learning.

The certificate is administered by the Center for Statistics and Machine Learning and under the direction of the certificate director (currently, Prof. Peter Ramadge). The academic program coordinator for the Center for Statistics and Machine Learning provides the administrative support.

In this program students learn the foundations of modern data science including computation, machine learning, and statistics, along with specific application domains; and to develop innovative methodologies for extracting information from data.

Artificial Intelligence Graduate Certificate at Stanford University provide a foundation and advanced skills in the principles and technologies that underlie AI including logic, knowledge representation, probabilistic models, and machine learning.

Students can pursue topics in depth, with courses available in areas such as robotics, vision, and natural language processing.

Cornell’s Machine Learning certificate program equips students to implement machine learning algorithms using Python. Using a combination of math and intuition, students will practice framing machine learning problems and construct a mental model to understand how data scientists approach these problems programmatically. Through investigation and implementation of k-nearest neighbors, naive Bayes, regression trees, and others, students will explore a variety of machine learning algorithms and practice selecting the best model, considering key principles of how to implement those models effectively.

Students will also have an opportunity to implement algorithms on live data while practicing debugging and improving models through approaches such as ensemble methods and support vector machines. Finally, the coursework will explore the inner workings of neural networks and how to construct and adapt neural networks for various types of data.

Certificate in Artificial Intelligence Management at Georgetown University provides a unique opportunity for students to engage with thought leaders in technology and business strategy while exploring how applications of AI can be leveraged for a competitive advantage.

Using theoretical frameworks, models, and real-world case studies, students will think strategically about how organizational performance and value can be increased in the cognitive enterprise. Students will also gain insight into the legal, ethical, and policy issues that surround the decisions of leaders within today’s business landscape.

Specialized Certificate in Machine Learning Methods at Regents of the University of California will introduce students to the subject matter using a variety of tools including: Linear Algebra, Deep Learning, TensorFlow, and Deep Neural Networks (DNN).

Courses consist of both theoretical and practical skills complementing each other and hence enhancing the machine learning scientist abilities. These courses are designed and classified to train students further in the field of machine learning, as well as coordinating with other engineering disciplines and industrial practices.

The Machine Learning (ECE) graduate certificate provides comprehensive training and education on the foundations of machine learning and current software tools. Courses provide a methodological foundation for static and dynamic (i.e., changing over time) problems. The certificate prepares students to apply machine learning methods to a variety of application domains. The Machine Learning (ECE) graduate certificate is available both on-campus and online via the ECE-EDGE program.

Machine learning is the the ability for computers to detect patterns in data and use it to make predictions that is changing our world in profound ways. In this three-course certificate program, You will be prepared for the machine learning scientist or machine learning engineer role. You’ll study the underlying algorithms and statistical methods that are at the core of machine learning techniques. The department will also apply these practices using the most popular tools and platforms — along with your developing judgment and intuition — to address actual business needs and real-world challenges.

The Graduate Certificate in Artificial Intelligence is designed to prepare business leaders for the vast opportunities that AI technologies provide. AI is the next step in the evolution of business technology, fueled by advances in machine learning. Students will learn the fundamentals of machine learning, deep learning, and embedded systems, as well as how to apply them to AI's enterprise applications, such as the Internet of Things (IoT).

By completing the graduate certificate in machine learning for engineering applications, students will develop the capabilities required to apply current tools and appropriate approaches to solve complex problems in a variety of domains. Students will gain a greater technical understanding of the elements of machine learning, including algorithms, intelligent systems, neural networks, pattern recognition and deep learning.

The university recognize the importance of flexibility to those pursuing graduate education, especially to practicing engineers. That’s why they offer you the opportunity to complete our certificates on a full- or part-time basis. In an effort to support engineers completing their certificates, the Dean of the Opus College of Engineering is offering up to 5 tuition scholarship credits for those enrolled in a 12 credit certificate.

Financial markets have transformed entirely since the 2008 financial crisis. Now, technical and programming skills are required alongside the usual finance and traditional statistics knowledge. Financial analysts and data scientists are in great demand as financial services companies on Wall Street and beyond look to their quantitative teams to uncover new advantages and exploit new kinds of opportunities.

The Machine Learning in Finance certificate provides the technical and programming knowledge needed to shine in quant-oriented roles in finance, including the ability to develop new models and put them into production. Courses cover probability, programming, statistics and machine-learning techniques.