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.
Get more from your bioprocess data. In this intensive, four-day course, designed specifically for scientists and engineers in the biopharma industry, you’ll explore best practices for translating biopharmaceutical manufacturing data into reliable models and better decisions. Working with academic and industry experts, you’ll acquire strategies for improving manufacturing accuracy, enhancing regulatory efficiency, and refining bioprocess operations.

Learn to leverage the latest deep learning advancements to create innovative solutions and solve your organization’s pressing challenges. Over the course of two intensive days, you’ll explore actionable strategies for anticipating and addressing critical issues that can impact classification performance and other hurdles, and master cutting-edge machine learning tools that process data in different modalities, including text, images, and graphs. 

Acquire the fundamental machine learning expertise you need to immediately implement new strategies for driving value in your organization. This foundational course covers essential concepts and methods in machine learning, providing the basic building blocks required to solve real tasks. You’ll also gain a deeper understanding of the strengths and weaknesses of learning algorithms, and assess which types of methods are likely to be useful for a given class of problems.
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.
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.
Examine how the latest tools, techniques, and algorithms driving modern and predictive analysis can be applied to produce powerful results, even when using unstructured data. In this highly interactive course, you’ll gain insights into what kinds of problems these methods can and cannot solve, how they can be applied effectively, and what issues are likely to arise in practical applications, particularly in the healthcare field.
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.