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Elevate Your Autonomous Robot Knowledge.

Next Training:

May 14 - 16, 2024

MIT Media Lab, Cambridge MA


Learning Machines
Training Objectives 

Autonomous robots such as drones are increasingly leveraging machine learning methods to acquire new capabilities that enable them to perform tasks more flexibly and robustly. At the same time, applications of autonomous robots also have important ethical and policy considerations to consider as this exciting technology continues to expand and evolve. 

Accordingly, we consider how to design, train, and integrate autonomous robots into human-robot teams to better achieve mission objectives and reduce uncertainty especially with operatives in military and government functions.


Learning Machines Training is a team-based, hands-on learning experience created by the MIT Media Lab where participants work on a series of highly structured coding projects to build and interact with their own machine learning models applied to physical robots and virtual agents.


By the end of this exciting three-day course, participants will have:

Set Learning Machine Strategies.

Lead Learning Machine Tasks.

Asked Important Questions Around Autonomous Systems.

Received a Learning Machines Certificate of Completion.

Key Learning Objectives

How do autonomous
robots work?

  • Demystify AI Algorithms

  • Hands-on experience in building autonomous robot technologies

  • Appreciate what’s hard

What are the challenges
and opportunities in
autonomous robots?

  • Autonomous Robot/Agent Applications

  • More informed to set strategy

  • More informed to lead operations

How do you make

autonomous robots


  • Gain experience in Humans + Robots

  • Think through ethical considerations

  • Think through policy considerations


The 12 Learning Milestones Covered In This Training

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Supervised Learning.png

Supervised Learning

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Bias and Privacy 


Conversational  AI

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Reinforcement Learning

Human in the Loop.png

Training & Evaluation

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Ethics and Policy

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AI Leadership


Generative Media


Generative Code

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Responsible Design


AI, Culture & Change


This three-day workshop isn’t just a course, it’s an immersive learning experience! 


We hope you not only leave this course with deeper technical, operational, and strategic insights as to the challenges and opportunities of responsible autonomous robotic systems -- but also we hope you have a ton of fun and make new friends. Be warned! There will be a friendly team-based competition to bring it all together. So get ready to be in it to win it!


                                Professor Cynthia Breazeal

                                Lead Instructor and Principal Investigator


  • The description says this is an experimental course. What does that mean?
    At MIT, we believe the best way to learn about technology and their broader implications is through designing them first hand. This is a custom designed course for the Lead-Drive cohort of the MIT-USAF AI Education Research Pilot. We will be exploring how leaders and managers learn through team-based, project-based learning in this course. This is the first time the course will be offered, so we anticipate learning and iterating the course, the learning activities, and the technologies from participant feedback.
  • Do I need any prior coding experience to participate in this course?
    No prior coding experience is necessary. Our team has developed a number of tools for novice coders to support hands-on learning experience.
  • Do I need to bring any equipment, like my own laptop?
    No. We will provide all the equipment needed for the course.
  • Can I get a tour of the MIT Media Lab?
    Yes! We are delighted to offer a tour of the Media Lab on Day 2 of the course.
  • Must I sign the media release form to participate?
    No, it is totally up to you. The teaching staff will be asking your permission to video you during the course. These videos help MIT researchers analyze team-based learning and participant engagement with the course activities and topics. We might also interview some of the participants to better understand their experience with this style of project-based, team-based learning. Videos we make may also be used in presentations to describe the course or we may use video snippets on the course website to help future participants better understand what they will experience by taking this course. The lectures will be video recorded and will be made available to participants after the course.
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