Starts June 21
Intermediate level
Robotics
Foundations
Learn to read robots as physical systems: task, environment, sensors, actuators, autonomy stack, safety, economics, and deployment.
No magic
Demo vs deployment
Market and economics
Final dossier
What this course isThis course treats robotics as a physical, product, and market system. We unpack automation, physical AI, robot categories, sensors, actuators, perception, control, autonomy stacks, safety, economics, and deployment friction. No mandatory ROS, simulator, hardware, or coding: the goal is to read robotics demos, pitches, job posts, product pages, and real use cases like an adult in the room.
- Separate automation, robotics, physical AI, and ordinary software agents without mixing them into one myth
- Read a robot as a system: task, environment, mechanics, sensors, actuators, control loop, safety, and fallback
- Tell a demo from deployment: what the video proves, what it hides, and which metrics a pilot needs
- Map the robotics market: humanoids, quadrupeds, AMRs, warehouses, drones, surgical, inspection, agriculture, and service robots
- Reason about deployment economics: CapEx, OpEx, uptime, teleoperation, safety envelope, ROI, and cost of failure
- Build a capstone Robotics Dossier for a robot, niche, or company without pretending this is a ROS lab
Robotics Foundations
Who this track is for
Product leads, founders, and strategists who need to understand robotics pitches, markets, use cases, and deployment risks without engineering fog.
AI practitioners and technical managers who want to separate physical AI from ordinary software agents and see where models meet physics.
Analysts, VC, BD, and operations teams reading about Unitree, humanoids, quadrupeds, AMRs, and warehouse robotics who want to check public statements.
Adjacent engineers who need the vocabulary of robotics teams: sensors, control, ROS 2, fleet ops, safety case, uptime, and ROI.
Anyone not building a robot by hand yet, but who wants to talk about robotics with market, product, and engineering teams.
Program
Move from the robotics map to anatomy cards, autonomy stacks, market players, source review, safety, economics, and the capstone Robotics Dossier.
01
Robotics Map
02
Robot as a System
03
Robot Types and Jobs
04
How Robots See and Act
05
Software, Autonomy Stack, and Tooling
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Format
Short lessons, artifact-based practices, common-sense tests, and a capstone project instead of a heavy hardware lab.
- Bite-sized lessonsEach step gives you a mental model, a short check, and a concrete artifact.
- Lightweight practiceInstead of installing ROS, you build anatomy cards, stack maps, demo reviews, economics snapshots, and evidence reviews.
- Final Robotics DossierThe course converges into a concise memo: what the robot does, where the risk is, who pays, and which sources support the statement.
CommunityYou do not need to install a simulator, connect hardware, or write a control node. You move like a product-and-systems analyst: read a public robotics statement, unpack the robot layer by layer, check deployment reality, and leave one small artifact each time. By the end, those artifacts become your Robotics Dossier.
What you will do during the course
01
Review public robots
Take a demo, product page, or news item and separate evidence from promise.
02
Build system maps
Track task, environment, sensing, actuation, control, safety, remote ops, and economics.
03
Check deployment math
Look at uptime, payback, nearby humans, service model, and cost of failure, not only the technology.
What you leave with
Not a ROS engineering portfolio, but the vocabulary and reasoning style used in robotics products, funds, AI teams, and operations pilots.
Robotics literacy
Understand conversations about sensors, control, autonomy, fleet ops, teleoperation, safety, and deployment friction.
Demo review
Ask better questions about a video, pitch, job post, product page, or pilot.
Robotics Dossier
Use the final memo as a calm example of how you analyze a robotics case.