Acquire the skills you need to build advanced computer vision applications featuring innovative developments in neural network research. Designed for engineers, scientists, and professionals in healthcare, government, retail, media, security, and automotive manufacturing, this immersive course explores the cutting edge of technological research in a field that is poised to transform the world—and offers the strategies you need to capitalize on the latest advancements.
Enhance your knowledge of the quantitative and computational realms of data science through the lens of regression analysis. Over the course of five days, you’ll learn to maximize the power of your advanced computing methods and identify strategies for fitting your data to models. Alongside global peers, you’ll gain a deeper understanding of the underlying mathematical models that form the basis of data science—and learn which models work best in different circumstances.
Transform your organization's engineering capabilities with comprehensive AI implementation spanning the complete design-to-deployment pipeline, from LLM-driven parametric design through advanced manufacturing optimization, computer vision quality control, and real-world deployment strategies. In this intensive hands-on course, you'll join accomplished global peers to master deployable AI workflows, create neural surrogates for expensive simulations, implement MLOps practices with regulatory compliance, and build complete integrated systems using open-source tools – leaving with working template libraries and custom components ready for immediate organizational deployment.
Devavrat Shah
Lead Instructor
Devavrat Shah is a professor with the department of electrical engineering and computer science, MIT. He is a member of the Laboratory for Information and Decision Systems (LIDS) and Operations Research Center (ORC), and the Director of the Statistics and Data Science Center (SDSC) in IDSS. His research focus is on theory of large complex networks, which includes network algorithms, stochastic networks, network information theory and large-scale statistical inference.
Carlo Ratti is a Professor of Urban Technologies and Planning Director of the MIT SENSEable City Lab. In the last decade, Carlo has given talks around the world on the theme of Smart Cities, while his work has been exhibited in international venues including the Venice Biennale, New York’s MoMA, London’s Science Museum and Barcelona’s Design Museum.
Bernhardt L. Trout is the Raymond F. Baddour, ScD, (1949) Professor of Chemical Engineering at MIT. He received his S.B. and S.M. degrees from MIT and his Ph.D. from the University of California at Berkeley. In addition, he performed post-doctoral research at the Max-Planck Institute.
David Sontag
David Sontag joined the MIT faculty in 2017 as Hermann L. F. von Helmholtz Career Development Professor in the Institute for Medical Engineering and Science (IMES) and as Associate Professor in the Department of Electrical Engineering and Computer Science (EECS). He is also a principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL). Professor Sontag’s research interests are in machine learning and artificial intelligence.
Professor Suvrit Sra is an Associate Professor in the EECS department at MIT. He is also a core faculty member of the Institute for Data Systems and Society (IDSS) and PI in the Laboratory for Information and Decision Systems (LIDS).
Justin Solomon
Professor Justin Solomon is an Associate Professor of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, where he leads the Geometric Data Processing Group. His textbook, Numerical Algorithms, covers numerical methods for geometry, graphics, robotics, and other computational applications.
Ben Waber
Participating Instructor
Ben Waber is recognized worldwide as one of the leading thinkers at the intersection of management, data, workplace, and people. He is the President and co-founder of Humanyze and a visiting scientist at the MIT Media Lab, where he received his PhD. His research was named a Top 10 Emerging Technology by the MIT Technology Review and a Breakthrough Idea by the Harvard Business Review. He is the honorary chairman of the Japan People Analytics and HR Technology Association and an advisory board member at Accenture and HR.com. Waber was previously a senior researcher at the Harvard Business School.