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October 2025
November 2025
December 2025
January 2026
Tuesday, January 27, 2026
- All dayGAP Deferred Action Meeting.
- All dayNuts and Bolts of New Ventures - Not For Credit VersionThe nuts and bolts of preparing a New Venture Plan and launching the venture will be explored in this 37th annual IAP offering. The course is open to members of the M.I.T. Community and to others interested in entrepreneurship. It is particularly recommended for persons who are interested in starting or are involved in a new business or venture. Offered in January 2026 on Tuesdays, Wednesdays and Thursdays January 20, 21, 22, 27, 28, 29 6pm to 9pm Room 10-250. Persons interested need to sign up for the email list at nutsandbolts.mit.edu/email.php
- 10:00 AM2hMathematics of Big Data & Machine LearningEnrollment: Limited: Advance sign-up required Limited to 35 participantsAttendance: Participants must attend all sessionsPrereq: Matrix MathematicsBig Data describes a new era in the digital age where the volume, velocity, and variety of data created across a wide range of fields is increasing at a rate well beyond our ability to analyze the data. Machine Learning has emerged as a powerful tool for transforming this data into usable information. Many technologies (e.g., spreadsheets, databases, graphs, matrices, deep neural networks, ...) have been developed to address these challenges. The common theme amongst these technologies is the need to store and operate on data as tabular collections instead of as individual data elements. This class describes the common mathematical foundation of these tabular collections (associative arrays) that apply across a wide range of applications and technologies. Associative arrays unify and simplify Big Data and Machine Learning. Understanding these mathematical foundations allows the student to see past the differences that lie on the surface of Big Data and Machine Learning applications and technologies and leverage their core mathematical similarities to solve the hardest Big Data and Machine Learning challenges.This interactive course will involve significant interactive student participation and a small amount of homework. Those students who fully participate and complete the homework will receive a certificate of completion.The MIT Press book "Mathematics of Big Data" that will be used throughout the course will be provided.E-mail the instructor to sign up.Instructors:Hayden Jananthan - Research Scientist MIT Supercomputing Center - hayden.jananthan@ll.mit.eduJeremy Kepner - Fellow & Head MIT Supercomputing Center - kepner@ll.mit.eduSignup Deadline: Dec 15
- 3:00 PM2hHow to CAD (and VR) Almost Anything! - IAP 2026Workshop blurb:Ever wondered how are objects from our daily lives designed? How can we generate a computer 3D model of a classic iPod, a Play Station controller, or a LEGO Tower Bridge? What about designing the Taipei 101 tower? A banana? Or how about visualizing and interacting with these objects using VR? In this fun MIT IAP 2026 workshop, you will learn the skills to design and VR-visualize all of these, and much more!Split into 8 (6 CAD, 2 VR) 2-hour long sessions, the first half of each session will be spent learning new Autodesk Inventor and VR skills, while the second half will see the application of these new skills through in-class activities, with a focus on reverse engineering. In contrast to traditional mechanical design courses, this workshop places greater emphasis on the design process itself, understanding how we can plan and best leverage our available tools to arrive to our desired result. Thus, the sessions are less about following the instructions on an engineering drawing, and more about independent thinking and strategizing, reverse engineering an object into a 3D model. New to this edition of "How to CAD" are 2 sessions that will go through the process of visualizing 3D models using VR!Logistics:Please express your interest in this workshop by filling up the following form.You can find the "How to CAD Almost Anything" syllabus for this IAP 2026 here.
- 6:30 PM1hWomen's Basketball vs. CaltechTime: 7:00 PM ET (4:00 PM PT)Location: Pasadena, CA