Take a deep dive into the mathematical foundations of AI and machine learning. You’ll explore the math behind not only fundamental models and algorithms, but also recent innovations such as Transformers and Graph Neural Nets—and discover how these concepts relate to Python code and associated applications.
Autonomous robots. Self-driving cars. Smart refrigerators. Now embedded in countless applications, deep learning provides unparalleled accuracy relative to previous AI approaches. Yet, cutting through computational complexity and developing custom hardware to support deep learning can prove challenging for many enterprises—and the cost of getting it wrong can be catastrophic. Do you have the advanced knowledge you need to keep pace in the deep learning revolution?
Over the past eight years, the amount of computing required to run these neural nets has increased over a hundred thousand times, which has become a significant challenge. Gain a deeper understanding of key design considerations for deep learning systems deployed in your hardware.
An active area of research, reinforcement learning has already achieved impressive results in solving complex games and a variety of real-world problems. However, organizations that attempt to leverage these strategies often encounter practical industry constraints. In this dynamic course, you will explore the cutting-edge of RL research, and enhance your ability to identify the correct approach for applying advanced frameworks to pressing industry challenges.
Reinforcement learning (RL), is enabling exciting advancements in self-driving vehicles, natural language processing, automated supply chain management, financial investment software, and more. In this three-day course, you will acquire the theoretical frameworks and practical tools you need to use RL to solve big problems for your organization
A steady rise in the application of exponential technologies, primarily artificial intelligence and machine learning, has necessitated a deep understanding of and broad capabilities for driving business growth for business leaders and managers in an evolving global economy. The AI and ML: Leading Business Growth program is a unique opportunity to explore and excel at a global level, with a no-code approach, and the knowledge, tools and best practices needed to drive strategic business growth powered by AI and ML.
MIT Prof. Jinhua Zhao will be delivering this 2-day course in Tokyo, Japan. This course will focus on two forces driving the future of urban mobility: behavior and computation. We use a behavioral lens to examine mobility technologies such as automation, connectivity, sharing, and electrification, and demonstrate the power of integrating behavioral and computational thinking. We observe that travel behavior is emotional, social, and perceptual, and mobility service can be predictive, individualized, experimental, and multimodal.
MIT Professional Education is pleased to offer the Professional Certificate Program in Machine Learning & Artificial Intelligence. MIT has played a leading role in the rise of AI and the new category of jobs it is creating across the world economy. Our goal is to ensure businesses and individuals have the education and training necessary to succeed in the AI-powered future. This certificate guides participants through the latest advancements and technical approaches in artificial intelligence technologies such as natural language processing, predictive analytics, deep learning, and algorithmic methods to further your knowledge of this ever-evolving industry.
Las nuevas tecnologías y el cambio tecnológico están reescribiendo las reglas de todo: modelos de negocio, procesos, gestión de personas, productos, producción y servicios. Por eso, anticiparse a las tendencias tecnológicas y a los escenarios de disrupción ya no es una opción, sino una necesidad estratégica.
New technologies and technological change are changing the rules of everything: business models, processes, people management, products, production, and services.
It is therefore critical to stay ahead of technology trends and be able to anticipate disruptions, which explains the growing importance of the figure of the Chief Technology Officer across all industries: the person responsible for keeping the company ahead of the technology curve, anticipating technological trends and turning them into a competitive advantage for the organization.
This program is designed to prepare senior managers that want to ascend to the position of Chief Technology Officer.
Tommi S. Jaakkola
Tommi Jaakkola is a Thomas Siebel Professor of Electrical Engineering and Computer Science and the Institute for Data, Systems, and Society. He is also a member of the Computer Science and Artificial Intelligence Laboratory. His work pertains to inferential, algorithmic and estimation questions in machine learning, including large scale probabilistic distributed inference, deep learning, and causal inference.