Learning Robotics & Automation 100 Hands-on Labs ROS2 to AI Systems

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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 pipelines
Requirements
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 IDE
Description
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 fleets
Every 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 architecture
This 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 systems
This 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 Architecture
Homepage

https://www.udemy.com/course/robotics-automation-100-hands-on-labs-ros2-to-ai-systems

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