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The one-year learning plan ends, but learners continue in the AI+X Global Talent Community — with ongoing access to the network, events, and future opportunities.
Your year
Your pace. Your path.
No rigid schedule. Build the year around your goals — take the four parts in any order, double up when you're ready, or start your Journey early. Tap each one below to see what's inside.
Foundation
You can start with one Foundation project that matches your background — a good first step if you're new to AI. It leads straight into the field you want to focus on.
Time
2 months per project
You leave with
Foundation done, and your first finished project
Foundation
These projects build the skills every AI field is built on.
Foundation
A 12-step innovation process taking an AI+X idea from unmet need to a defensible build.
View Details →Foundation
Build vision systems that reconstruct 3D scenes, detect objects, and synthesize images.
View Detail →Foundation
Reconstruct and render 3D scenes, avatars, and physical simulation with neural representations.
View Detail →Foundation
Build and evaluate language models for classification, entity recognition, and semantic similarity.
View Detail →Concentration
This is where you choose your direction. Complete two projects in your concentration, and the certificate is yours. In each project, you pick one topic to work on.
AI + Foundation
Start from the ground up. Build the skills every AI field stands on — one real project at a time.
AI + Business & Finance
Turn business and money questions into models that help people make real decisions.
AI + Physical Intelligence
Teach robots and machines to see, decide, and act in the messy real world.
AI + Health Tech
Use AI on health and biology data — held to the same high standards as real medical research.
Format
Two months, with live classes
Team
3–6 students
Time
6–8 hrs per week total
Choice
One topic per project
More projects sit outside the concentrations — including quantum computing. They are taken and reviewed like any other project. They just do not count toward your certificate.
Research or Industry
One year, one Journey. Your work becomes research — or industry experience.
You write a real research paper — and submit it to a journal or conference.
You earn an industry internship — working with a real company, remote, wherever you are.
You pick one Journey for the year. Change your mind once, in your first three months — after that, your path is set.
Who teaches
Every project is designed and taught by a project lead — working researchers and industry experts from the MIT AI+X ecosystem, with project work from companies such as NVIDIA, Genentech, and Bloomberg. We show their lab and role here; you get their names once you enroll.
3D
Computational Design & Fabrication Group
Ph.D. Researcher · MIT CSAIL
Differentiable physical simulation and computational design. Published at SIGGRAPH, CVPR and ACM TOG. Leads the NVIDIA Project.
RBT
Robotic Manipulation Group
Ph.D., MIT CSAIL · CTO, robotics startup
Manipulation and state estimation during contact. First place, Amazon Robotics Challenge stowing task. Leads the Boston Dynamics Project.
ECO
Digital Economy Lab
Research Scientist · Stanford University
Seven years as a financial economist at the Federal Reserve Bank of Richmond. Leads the Bloomberg Project.
MED
Clinical Imaging AI
Senior Imaging Scientist · Novartis
Leads technical strategy for integrating AI into clinical trials. Two medical-device startups founded. Leads the Novo Nordisk Project.
BIO
Regenerative Bioengineering
Bioengineering Researcher · Stanford University
Comparative systems biology of regeneration. Co-creator of a 20-cent centrifuge recognized by INDEX: Design to Improve Life. Leads the Genentech Project.
QNT
Theory of Quantum Systems Group
Researcher · University of Oxford
Quantum error correction and variational algorithms. Previously at a neutral-atom quantum computing startup. Leads the IBM Qiskit Project.
Affiliations listed are each individual's own and do not imply institutional endorsement of BlendED.
On campus
Cambridge is where you finish the work you've been building. Two weeks in Cambridge, Massachusetts — present and defend what you built, in the room with the project lead who reviewed your work and the team you built it with. Steps from Moderna, Google, Amazon, and IBM Research.
01
One evaluated project, finished on site
What you built online, you finish face-to-face — working side by side with your team, then presenting live to the project lead who taught it.
02
Visits inside Kendall Square
You walk into the labs and companies around you, and see how this work really gets done — right where it happens.
03
A small-group roundtable
A sit-down conversation with researchers and founders, kept small enough that you get to ask your own questions — and get real answers.
04
Meet your team in person
You finally meet the teammates you built with online — and join the Global Talent Community you stay part of long after the two weeks end.
Students
Students come from engineering, life sciences, international relations and business analytics.
Coming from a humanities background, AI felt inaccessible at first. The foundation course gave me the confidence to enter the field, and the AI+X projects showed me how to apply AI thinking to new domains. For the first time, I could see how my background connects to emerging technologies.
Alice S.
B.S. International Relations, The University of Tokyo
The structured journey from AI foundations to applied PBLs completely changed how I see my future. Through the AI + Computer Vision in Biotech project, I didn't just learn new tools — I validated that Medical AI is the field I want to build my career in.
John J.
B.S. Electrical and Electronic Engineering, Yonsei University
The AI+Biotech concentration gave me both breadth and depth. I could choose projects aligned with my interests while applying machine learning in real-world biotech contexts. It felt less like coursework and more like building something that actually matters.
Yasmeen T.
B.Sc. (Hons) Life Sciences, National University of Singapore
Plans
The difference between the plans is what you leave with. Everyone builds the project portfolio — your goal decides whether you add the research paper or the internship.
Do I need coding or AI experience?
+
It helps, but you don't need it. The Foundation projects have beginner tracks made exactly for this, and your project lead works with you along the way.
How much time does a program take each week?
+
Plan for 6–8 hours a week across a two-month project, including one live meeting. Most of the rest you do on your own schedule, and meeting times work across time zones.
Does the plan cover housing, travel and visas on campus?
+
No. Housing, travel, and visa costs are separate. We offer an optional housing package, provide the documents you need for your visa application, and supervise all activities on site for the full two weeks.
Can I switch between Research and Industry?
+
Yes — once, in your first three months, arranged with us. After that your Journey is set for the year, because your support team and your plan are built around it.
What if we need to pause?
+
Yes — there is a clear process we agree on when you sign. First, a 14-day grace period. Then a hold that pauses deadlines while you keep access to materials. Then one formal pause of up to 60 days per year. Anything you have completed — projects and certificates — stays yours.
Is the internship guaranteed?
+
No — you earn it. The criteria are published before you start, and your coach works with you toward them all year. What we promise is the structure: real projects, written evaluations, and a clear, public bar.
What if I don't have a clear goal yet?
+
That's fine. Your coach helps you explore, try different AI fields, and pick a direction. Some students join just to find out if a field is right for them — and leave knowing.
Apply now — the next sessions start in September. We build your plan around what you already know and what you have already made.
