MIT Short Course Admissions for 2023-2034: Apply Now

MIT Short Courses offer a diverse range of subjects to cater to different interests and goals

MIT Short Courses are intensive, non-credit courses that provide individuals with the valuable opportunity to learn from esteemed MIT faculty and researchers. Covering a wide range of disciplines including business, engineering, science, and technology, these courses offer participants numerous benefits. By enrolling in an MIT Short Course, individuals can access cutting-edge knowledge and skills, allowing them to stay ahead in their respective fields. Additionally, participants have the chance to network with professionals from around the world, fostering valuable connections and collaborations. Moreover, taking an MIT Course can enhance career prospects by equipping individuals with the latest insights and expertise. Embarking on an MIT Short Course journey can provide individuals with an enriching educational experience and contribute to their personal and professional growth.

Predictive Multiscale Materials Design- Markus J. Buehler will be leading a course titled "Predictive Multiscale Materials Design" at MIT from June 3 to June 7, 2024. This on-campus course falls under the categories of Data Modeling & Analytics, Design & Manufacturing, and Innovation. The course aims to provide participants with insights and techniques for predicting and designing materials at multiple scales. By attending this course, participants will have the opportunity to learn from Markus J. Buehler, a renowned expert in the field. The course fee is set at $4500, and the course is open to interested individuals. This immersive learning experience at MIT promises to equip participants with valuable knowledge and skills in the field of multiscale materials design.

Tribology: Friction, Wear, and Lubrication- MIT will be offering a course on "Tribology: Friction, Wear, and Lubrication" from June 10 to June 14, 2024. Led by Nam Pyo Suh and Nannaji Saka, this on-campus course falls under the category of Design & Manufacturing. The course will focus on the study of tribology, which involves understanding the principles of friction, wear, and lubrication. Participants will have the opportunity to learn from these distinguished experts in the field. The course fee is set at $4500, and the course is open to individuals interested in gaining a deeper understanding of tribology and its applications in design and manufacturing. By attending this course at MIT, participants can expand their knowledge and gain valuable insights into the field of tribology.

Breakthrough Innovation: Creating Value in Times of Uncertainty- MIT will be hosting a course titled "Breakthrough Innovation: Creating Value in Times of Uncertainty" from July 8 to July 10, 2024. This on-campus course focuses on the subject of innovation and is open to participants from all backgrounds. Led by Michael Davies and Blade Kotelly, the course aims to provide attendees with knowledge and strategies for generating breakthrough innovations, even in times of uncertainty. By attending this course, participants will have the opportunity to learn from these experienced experts in the field of innovation. The course fee is set at $3600, and it offers individuals the chance to explore and develop their innovation skills in a dynamic learning environment at MIT.

Graph Algorithms and Machine Learning– MIT will be conducting a course on "Graph Algorithms and Machine Learning" from June 3 to June 6, 2024. This live virtual course falls under the category of Data Modeling & Analytics. Led by Julian Shun, the course will focus on the intersection of graph algorithms and machine learning. Participants will have the opportunity to learn about the application of graph algorithms in the context of machine learning and gain insights into how these two fields can complement each other. The course will be conducted in a live virtual format, allowing participants to access the course materials and interact with the instructor remotely. The course fee is set at $2500, and the course is open to individuals interested in exploring the integration of graph algorithms and machine learning in data modeling and analytics. This course offers a unique opportunity to delve into the cutting-edge field of graph algorithms and machine learning with guidance from an expert in the field.