Join the network of engineers, researchers, and developers.
live engineering sessions of real world project builds, well documented step-by-steps to develop context engineering input for agent training and LLM fine-tuning.
Kick off your sprint program with this foundational session, where you'll learn to set up Cursor, Git, Docker, Linux, virtual computers, and servers, mastering the essential tools for software development.
Dive into the core of machine learning by training regression models, LSTMs, transformers, and CNNs, laying a solid foundation for building advanced machine learning systems.
Explore mathematical modelling, mechatronic system design and simulation with MATLAB, Python, Wolframe in this third week of the sprint program.
Protoype with OpenCV, YOLO and transformer models for segmentation, classification, and identification in robotic and generative AI applications.
Setup and manage Infrucstructure to to maintain AI models in training, fine-tuning, serving with FastAPI and AWS Foundry.
Simulate open source SLAM tools using NVIDIA omniverse and Isaac Sim running on a remote RTX containers.
Master rigid body modeling, URDF/SDF file formats, and end-to-end 3D printing workflow for robotic system prototyping.
Apply autonomous robotics to real-world farming scenarios with data-driven decision making and crop optimization.
Resource-constrained real-time software development practices with foundational embedded system development practices.
Design intuitive interfaces and collaborative workflows between autonomous systems and human operators.
Develop intelligent battery management for extended autonomous operation with predictive maintenance capabilities.
Build and deploy production-ready RAG pipelines for AI agents with advanced retrieval and generation capabilities.
Integrated simulation of robotic manupulators and mobile robots for precise agricultural tasks like harvesting, pruning, and maintenance operations.
Build adaptive systems that respond to changing weather conditions and environmental challenges.
Complete your autonomous tractor project with comprehensive testing, validation, and deployment strategies.
Real-world open source projects that combine AI, robotics, and engineering innovation
A fully open-source autonomous agricultural tractor system that combines robotics, AI, and sustainable technology to revolutionize farming practices. Built with ROS2, computer vision, and LLM integration for intelligent agricultural operations.
Embed Large Language Models for natural language based human machine interaction, teaching the tractor to understand and respond to human commands.
Design efficient batter & thermal management systems, motor controllers, and regenerative braking for sustainable agricultural operations
Develop computer vision for crop monitoring, soil analysis, and precision farming with autonomous navigation
Implement fail-safe systems, emergency protocols, and robust mechanical design for safe autonomous operation
Onboard compute lets the tractor work remotely, even with low internet coverage.
Real-time 3D simulation and digital twin visualization powered by NVIDIA Omniverse for autonomous system monitoring and control
Set up development environment, establish project structure, and begin basic chassis design with motor integration.
Design and implement electric powertrain with battery management system and motor controllers.
Integrate GPS, IMU sensors, and implement basic autonomous navigation algorithms.
Develop crop monitoring and obstacle detection systems using computer vision and machine learning.
Embed Large Language Models for natural language task planning and adaptive decision-making.
Implement fail-safe mechanisms, emergency protocols, and comprehensive safety validation.
Complete system integration, conduct field testing, and optimize performance parameters.
Final validation, documentation completion, and deployment of the autonomous tractor system.
A comprehensive open-source DevOps platform that combines AI agents, automation, and security to streamline development and deployment workflows. Built with FastAPI, Next.js, and local-first architecture.
Manage apps, servers, and deployments using a local-first RAG-powered DevOps agent.
Over 90+ Makefile CLI commands for managing deployments, rollbacks, secrets, and more.
Electron-based desktop app with real-time dashboard, app manager, and environment controls.
Retrieve answers from indexed docs, logs, and configs using locally hosted embeddings.
Run secure terminal sessions (including SSH) directly inside the app interface.
Manage per-app and per-team secrets using Ansible Vault integration and key rotation.
Supports GitHub Actions, webhooks, and environment-specific deployments with rollback safety.
Modular backend with FastAPI tool adapters, local LLM integration, and external service hooks.
Completed full-stack architecture, built MVP UI with ShadCN & Next.js, initialized FastAPI backend, CLI automation with Makefile, Ansible integration, secret vaults, and embedded DevOps RAG agent. Core system is working locally and remotely.
Connect the RAG agent to your local tools (Make, Ansible, logs, vault) and initialize AI pipeline.
Design and finalize the professional UI using ShadCN and Next.js with sidebar, terminal, and panels.
Embed a live terminal with SSH session management and support for secure CLI commands.
Introduce user auth, secrets vaults, and permission-based team environments with audit logging.
Connect PostgreSQL + Neo4j for long-term memory, and support fine-tuned or local LLMs for offline use.
Bundle the desktop agent into an Electron app with fast deployment to any VPS (or local device).
Polish documentation using MkDocs with complete CLI, agent, and vault workflows explained.
Finalize repo structure, prepare a launch video/demo, and go live with public GitHub and marketing page.
AI and robotics are projected to transform every industry, automating tasks, creating new opportunities, and changing the way we live and work. The future belongs to those who understand and build these technologies.
*Source: World Economic Forum, McKinsey Global Institute
"Building is the best way to learn. Most courses teach technicalities, syntax, tools, and theory but rarely focus on solving meaningful problems. Here, we flip that. It is okay not to know everything. You will learn to use your imagination, lean into uncertainty, and let AI support you with the technical heavy lifting. I started this platform not as a teacher, but as a builder. You will not just watch from the sidelines—you will be in the trenches with me, working on real-world projects that push both of us. We learn together. We reflect. And we build."
Empower students to build real-world AI and robotics solutions for a better, more sustainable future.
To create a global community where anyone can learn, innovate, and lead in the age of intelligent machines.
Founded in 2024, we've grown from a small community to a global platform, helping thousands of students build the future of AI and robotics.
Everything you need to know about our robotics and AI courses, from prerequisites to career outcomes.
Still have questions? We're here to help!
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