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Robotics & Automation 100 Hands-on Labs ROS2 to AI Systems
Published 5/2026
Created by Dar Al Taqniya
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 112 Lectures ( 7h 32m ) | Size: 2.2 GB
From beginner robotics to production-grade autonomous robotics, ROS2 systems, and AI-powered fleet engineering.
What you'll learn
Build production-grade robotics systems using ROS 2, Linux, and distributed architectures Design scalable robotic fleet management systems for warehouses, logistics, and industrial environments Architect industrial IoT and automation systems using MQTT, OPC UA, Modbus, and CAN Bus Containerize and orchestrate robotics workloads using Docker and Kubernetes at the edge Design and deploy autonomous robots with real-world navigation, SLAM, and sensor fusion pipelinesRequirements
This course is designed to be accessible, but production-grade engineering is required. Basic Requirements Basic understanding of programming (Python recommended) Willingness to learn Linux command line Willingness to learn Linux command line Software Requirements Ubuntu 22.04 LTS (recommended primary OS or VM) Python 3.10+ Docker & Docker Compose ROS 2 Humble Hawksbill VS Code or similar IDEDescription
This course contains the use of artificial intelligence.
Most robotics courses in the market today are built for demonstration-not deployment.
They teach you how to move a robot arm, simulate a TurtleBot, or run a basic ROS node. But in 2026, that is not enough.
The real world does not run "vibe robotics."
It runsproduction-grade autonomous systems-distributed fleets of robots, edge AI pipelines, industrial IoT networks, secure communication layers, and cloud-native orchestration systems that must never fail in warehouses, hospitals, factories, and defense environments.
This is the gap this course is built to destroy.
The Solution: A 100-Lab Production Engineering Journey
This is not a theory course. It is a100-lab engineering system buildout.
You will start from zero-setting up a robotics workstation, mastering Linux and Python foundations-and progressively evolve into building
ROS 2-based robotic systems Industrial IoT pipelines Autonomous navigation engines Edge AI inference systems Kubernetes-based robotics infrastructure Secure, compliant, observable robotic fleetsEvery module is designed like a real engineering pipeline, not an academic lecture.
What's Inside the System
Module 1-2: Foundations + ROS 2 Core
You establish your robotics engineering environment and master ROS 2 architecture, nodes, topics, actions, and middleware (DDS). This is your operational base.
Module 3: Embedded Systems
You connect real-world hardware concepts: sensors, microcontrollers, CAN Bus, GPIO, and real-time constraints.
Module 4-5: Vision + Navigation
You build perception pipelines using OpenCV, YOLO, LiDAR, SLAM, and Navigation2 to create fully autonomous mobile robots.
Module 6: Industrial IoT
You integrate real industrial protocols (OPC UA, MQTT, Modbus) and design smart factory systems.
Module 7: DevOps + Kubernetes for Robotics
You containerize robotics workloads and deploy them at the edge using Kubernetes, Terraform, and GitOps workflows.
Module 8: Security & Compliance
You implement Zero Trust robotics systems with encrypted communication, identity federation, secure OTA updates, and compliance-aware logging.
Module 9: Observability & Fleet Operations
You build production monitoring systems using Prometheus, Grafana, and OpenTelemetry-managing entire fleets of robots in real time.
Module 10: AI + Digital Twins
You move into advanced robotics intelligence-edge AI, reinforcement learning, digital twins, and multi-robot coordination systems.
The Climax: Lab 100 (The Enterprise Capstone)
Lab 100 is where everything converges.
You will design and deploy anEnterprise Autonomous Robotics and Automation Platform-a real-world-grade system that includes
Multi-robot fleet orchestration Kubernetes edge infrastructure ROS 2 distributed robotics network Secure telemetry pipelines AI-powered perception systems Digital twin simulation environments Full observability and incident recovery systems Zero Trust, compliance-aware architectureThis is not a demo.
This is aPhD-level production system architecture challenge.
By the end, you won't just "know robotics."
You will be able todesign and deploy robotics ecosystems used in real industries.
Why Enroll Now?
The robotics industry is shifting fast.
Companies are no longer hiring people who "know ROS."
They are hiring engineers who can
Deploy fleets of robots Manage edge infrastructure Secure industrial systems Build observability pipelines Integrate AI into physical systemsThis course is built for that exact shift.
If you want to move from learner → engineer → systems architect, this is your path.
Who this course is for
The Aspiring Robotics & AI Engineer The Industrial Automation Engineer The Senior Developer Moving into Systems ArchitectureHomepage
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