This course is also offered in a Live Online format, meeting simultaneously with the on-campus cohort.
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.
This course may be taken individually or as part of the Professional Certificate Program in Design & Manufacturing or the Professional Certificate Program in Machine Learning & Artificial Intelligence.
Over the next few decades, engineering organizations worldwide will integrate artificial intelligence throughout their complete design-to-deployment workflows, transforming how complex products are conceived, validated, manufactured, and deployed. This transformation is already accelerating – from LLM-driven parametric design and neural surrogates replacing expensive simulations to computer vision quality control and real-time digital twin optimization. To stay competitive, professionals need comprehensive mastery of AI implementation strategies across the entire engineering pipeline – and practical experience deploying them with regulatory compliance and organizational readiness.
This course provides intensive hands-on training in complete AI engineering workflows from concept through manufacturing to deployment. Over five days, you will master how AI transforms each stage of the engineering process while building deployable implementations for immediate organizational use. In this course, you will also:
• Learn how AI drives manufacturing optimization including toolpath generation, CNC machining, and sustainability metrics
• Master LLM integration for automated design generation, neural surrogates for simulation replacement, and MLOps practices
• Implement computer vision systems for quality control, sim-to-real calibration for reliable deployment, and complete workflow integration with custom components
Certificate of Completion from MIT Professional Education
The type of content you will learn in this course, whether it's a foundational understanding of the subject, the hottest trends and developments in the field, or suggested practical applications for industry.
How the course is taught, from traditional classroom lectures and riveting discussions to group projects to engaging and interactive simulations and exercises with your peers.
What level of expertise and familiarity the material in this course assumes you have. The greater the amount of introductory material taught in the course, the less you will need to be familiar with when you attend.