Private corporate batches, live online cohorts and 1-on-1 mentoring in ROS 2 robot software — perception, navigation, control and simulation, deployed onto real hardware — taught by a practitioner who runs it in production.
20 years across DevOps, SRE and Security · 10,000+ engineers trained · Trained teams at JPMorgan Chase, Verizon, Nokia and the World Bank
Principal DevOps Engineer & Architect
Rajesh teaches Robotics as a software engineering discipline with physical consequences: the ROS 2 node graph and its three communication patterns, DDS quality-of-service settings and the mismatches that silently drop messages, tf2 transform trees and the frame errors behind most navigation bugs, and launch, parameter and lifecycle management for systems with dozens of nodes. Sessions run everything in Gazebo before hardware, cover Nav2 costmap and controller tuning, MoveIt planning for manipulation, rosbag2-driven debugging of failures you cannot reproduce live, and the deployment and CI practices that keep a robot fleet updatable rather than hand-flashed.
Twenty years across DevOps, SRE and Security, in principal and architect roles at PayPay, SoftwareAG, ServiceNow, JDA Software, Intuit, Adobe and others. He has trained engineers at JPMorgan Chase, Verizon, Nokia, the World Bank, VMware, Oracle, Mercedes-Benz and Airbus — more than 10,000 people personally. He teaches what he runs, not what he reads.
You are booked with a named engineer, and that is who turns up. Marketplaces and larger providers rotate whoever is free, so the person who sold you the agenda is rarely the person teaching it.
The same trainer is available for the next engagement, which matters when a team builds on what it learned last time.
Your batch is assigned a named trainer before it starts, and that is who teaches it. See the full faculty.
Engagements are matched on the tool, not the calendar. For Robotics that means a trainer who has run it in production — ROS 2 robot software — perception, navigation, control and simulation, deployed onto real hardware — rather than whoever is free that week. You are told who is teaching before you commit, and that person is on the discovery call that shapes the agenda.
Where a batch is large enough to need a second trainer, the pairing is declared up front. The lead trainer stays accountable for the syllabus and the assessment either way.
Principal DevOps Engineer & Architect
Twenty years across DevOps, SRE and Security in principal and architect roles at PayPay, SoftwareAG, ServiceNow, JDA Software, Intuit, Adobe, IBM/Emptoris, Ness, MindTree and Accenture. He has trained more than 10,000 engineers personally, at organisations including JPMorgan Chase, Verizon, Nokia, the World Bank, VMware, Oracle, Mercedes-Benz and Airbus. He teaches what he runs, not what he reads.
Teams of 8–30
Custom agenda, your timezone, onsite or online, NDA-friendly.
Request a quoteIndividual engineers
A private instructor and a curriculum built around your goal.
₹99,999Individuals who want peers
Scheduled batch, max 8 to 10 hours of live instruction.
₹34,999A private batch starts with a discovery call. We look at the stack you actually run — the CI system, the cloud, the constraints — and map the agenda onto it, so examples use your topology rather than a generic one.
Delivery is onsite at your premises, live online, or hybrid, scheduled around your release calendar rather than ours. Batches run 8 to 30 engineers.
Every attendee leaves with recordings, slides, lab repositories and a completion certificate. You receive an attendance and assessment report. Invoicing supports PO and GST.
Talk to us about a private Robotics batchRobotics is the engineering discipline of building machines that sense their environment, decide what to do and act on the physical world. In software terms it is a distributed systems problem with hard real-world constraints: many processes producing and consuming sensor data at different rates, a shared notion of time, a shared notion of where every part of the machine is in space, and no ability to retry a movement that has already collided with something.
Modern Robotics software is overwhelmingly built on ROS 2, a middleware and toolset rather than an operating system. ROS 2 gives you a node graph communicating over DDS with configurable quality-of-service, three interaction patterns — topics for streaming data, services for request/response, actions for long-running goals with feedback and cancellation — and a set of conventions that let independently written components compose. Around that sit the pieces every robot needs: tf2 for coordinate frame transforms, URDF for robot description, Nav2 for autonomous navigation, MoveIt for manipulation planning, and rviz2, rosbag2 and Gazebo for visualisation, recording and simulation.
Underneath the middleware sit the disciplines that make a robot work at all. Kinematics and transforms describe where the arm or the base actually is. Control loops — PID at the simple end, model-predictive at the complex end — turn a desired state into motor commands. Perception turns camera, lidar and IMU data into a usable world model, and state estimation fuses those noisy streams with Kalman or particle filters. Simulation is not optional: almost all Robotics development happens in Gazebo or Isaac Sim first, because hardware iteration is slow and breakage is expensive.
Robots left the caged cell. Warehouse AMRs, agricultural platforms, inspection drones, surgical assistants, last-mile delivery units and collaborative arms all now operate in environments they share with people, which means autonomy, perception and safety software rather than a fixed program repeated on a jig. That shift moved the centre of gravity in robotics hiring from mechanical and electrical engineering towards software.
ROS 2 consolidated the field. Where the last decade fragmented across proprietary stacks, most new commercial platforms now build on ROS 2 with DDS underneath, which makes the skill portable across employers and domains in a way it previously was not. At the same time, hardware became affordable — a capable development platform now costs less than a workstation did — so teams can prototype before committing to a build.
The hiring gap is specific. There are plenty of engineers who can write Python and plenty who understand control theory, and comparatively few who can debug a tf2 tree that has drifted, tune a Nav2 costmap so a robot stops oscillating in a doorway, work out why a DDS quality-of-service mismatch is silently dropping messages, and then get all of it running reliably on a constrained onboard computer.
What a robot software stack actually contains, from sensor driver to behaviour. The sense-plan-act loop, why the field converged on ROS 2, the DDS middleware underneath, and the workspace and build tooling everything else depends on.
Topics: Sense, plan, act — and where latency kills each stage · ROS 2 architecture: nodes, the graph, and DDS discovery · ROS 1 versus ROS 2 and what the migration changed · Workspaces, packages, colcon and the underlay/overlay model · Command-line tooling: ros2 node, topic, service, param, doctor · Distributions, versioning and choosing a target release
The communication layer in depth, because almost every mysterious robot bug lives here. Publishers and subscribers, services, actions with feedback and cancellation, custom interface definitions, and the DDS quality-of-service settings that decide whether your messages arrive at all.
Topics: Writing nodes in Python and C++ · Publishers, subscribers and message types · Services for request/response, and when they are the wrong choice · Actions: goals, feedback, results and cancellation · Custom msg, srv and action definitions · Quality of service: reliability, durability, history and depth · QoS incompatibility and how to spot it before it wastes a day · Executors, callback groups and multi-threading
Where the robot thinks it is. Coordinate frames, rotations and the tf2 tree that ties them together; URDF and Xacro to describe links, joints and sensors; forward and inverse kinematics; and the timestamp and frame errors responsible for a large share of navigation failures.
Topics: Coordinate frames, rotation representations and quaternions · tf2: broadcasters, listeners, buffers and the transform tree · Static versus dynamic transforms, and the standard frame conventions · Debugging a broken or drifting tf tree · URDF links, joints, inertia, collision and visual geometry · Xacro for parameterised robot descriptions · robot_state_publisher and joint states · Forward and inverse kinematics for arms and mobile bases
Running a whole robot before the hardware arrives. Gazebo worlds, sensor and physics plugins, launch files that bring up dozens of nodes with the right parameters, lifecycle nodes for deterministic startup, and simulation time so everything agrees on the clock.
Topics: Gazebo worlds, models and physics configuration · Simulated sensors: camera, depth, lidar, IMU · ros_gz bridging between simulation and the ROS graph · Python and XML launch files, arguments and substitutions · Parameters, YAML parameter files and parameter overrides · Managed lifecycle nodes and deterministic bring-up · use_sim_time and clock synchronisation · Composable nodes and intra-process communication
Turning noisy sensor data into a world model, and a world model into motion. Camera and lidar processing, sensor fusion with Kalman and particle filters, odometry sources and their drift characteristics, and closed-loop control from PID up to model-predictive.
Topics: Camera models, calibration and image pipelines in ROS 2 · Lidar and point cloud processing basics · IMU data, bias and integration drift · Wheel odometry and its failure modes · Kalman, extended Kalman and particle filters for fusion · robot_localization for multi-sensor state estimation · PID control: tuning, saturation and anti-windup · Trajectory generation and an introduction to model-predictive control
The two application stacks most robots need. Nav2 for mobile autonomy — SLAM, costmaps, global and local planners, controllers, behaviour trees and recovery — and MoveIt for arms, with collision-aware planning, grasping and execution monitoring.
Topics: SLAM and map building with slam_toolbox · AMCL localisation against a known map · Nav2 architecture and the behaviour tree navigator · Global and local costmaps, layers and inflation · Planners, controllers and recovery behaviours · Tuning Nav2 for narrow spaces, doorways and oscillation · MoveIt configuration, planning groups and kinematics solvers · Collision checking, grasp planning and execution monitoring
Getting off the simulator and staying maintainable. Driver integration and real-time considerations on onboard compute, rosbag2 for reproducing failures you cannot recreate live, safety and emergency stop design, containerised deployment, CI for robot software and over-the-air updates across a fleet.
Topics: Hardware interfaces, ros2_control and driver integration · Real-time constraints and where a Linux scheduler is not enough · Running on constrained onboard compute and profiling the graph · rosbag2 recording, replay and offline analysis · Diagnostics, logging and health monitoring · Safety design: emergency stop, watchdogs and fail-safe states · Containerising a ROS 2 stack and cross-compiling for ARM · CI, simulation-based testing and over-the-air fleet updates
We rebuild the agenda around the tools you actually run.
Request a custom agendaBuild a multi-node system, break it with a reliability and durability mismatch, and learn to identify the symptom before it costs an afternoon.
Take a robot description with a missing link and a timestamp offset, diagnose the transform tree and restore correct sensor-to-base geometry.
Bring up a simulated robot with sensors, controllers and parameters from a single command, so another engineer can reproduce it exactly.
Combine wheel odometry and IMU through robot_localization and quantify how much position drift the fusion actually removed over a fixed route.
Diagnose and tune a Nav2 stack that oscillates in narrow spaces — costmap inflation, controller parameters and recovery behaviours.
Build a robot that autonomously navigates to a goal, perceives an object, plans a collision-free grasp with MoveIt and recovers cleanly on failure.
Billed yearly at ₹9,996
Max 8 to 10 hours of live instruction
Full program, private instructor
8–30 engineers · custom agenda · onsite or online · PO and GST invoicing
Refunds. If we cancel or postpone a cohort, you get a full refund within 15 days. There is no money-back guarantee otherwise.
Terms. Course material remains licensed to the attendee. Read the terms.
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Certificate of completion
Very good training session. Well explained from the basics to the complex concepts. Also tried to cover practicals and demos within the 3 hour sessions. The learning content and videos are of a great deal of help.
Basics explanation was exemplary from Rajesh where he dealt with complicated topics to be simple. Great learning stuff personally for me.
Very detailed explanation and has lots of patience in attending the questionnaire. Thanks again for your wonderful sessions.
Good discussion, helped us to understand different tools in SRE.
Got good lab sessions which kept the new DevOps tool learnings to the point and it helped a lot in my career.
I took Terraform training with the tutor named Mithilesh. I requested to tailor the course curriculum for my needs. He did an excellent job of showing me how to write the Terraform script per the instructions provided.
| What matters | YouTube + blogs | Generic online course | Freelance marketplace | DevOpsSchool |
|---|---|---|---|---|
| Named practitioner | No | Rarely | Varies per booking | Yes — same trainer each time |
| Production experience | Unknown | Unknown | Unverified | 20 years, named employers |
| Custom agenda | No | No | Sometimes | Built from your stack |
| Onsite delivery | No | No | Sometimes | Yes |
| Lab environment | None | Sandbox that expires | Varies | Your own cloud — skill goes with you |
| Assessment | None | Quiz | Rarely | Assignments + capstone per module |
| Per-attendee certificates | No | Sometimes | Rarely | Yes |
| Corporate invoicing | No | Limited | Varies | PO and GST |
| Post-training support | None | Forum, time-limited | None | Lifetime forum access |
Tell us the team, the stack and the timeline. You'll get a straight answer, not a sales sequence.
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