I would like to do robotics software engineer course from udacity
But it cost me 1 lakh per year with 2 phase(around 45k, 67k)
I though about reading the syllabus
learning the projects, practicing with
---

• Introduction To Robotics

  In this course, you'll get an introduction to your Nanodegree program, and explore the three essential elements of robotics: perception, decision making, and actuation. You'll also build your first project, which is modeled after the NASA Mars Rover Challenge.

  SEARCH AND SAMPLE RETURN

• ROS Essentials

  ROS provides a flexible and unified software environment for developing robots in a modular and reusable manner. In this course, you'll learn how to manage existing ROS packages within a project, and how to write ROS Nodes of your own in Python.

Kinematics

Movement is one of the most exciting elements of building a Robot that interacts with the physical world. In this course, you'll learn to control a robotic arm with six degrees of freedom to perform pick and place actions using Inverse Kinematics.

• ROBOTIC ARM: PICK AND PLACE

• Perception

  Robots perceive the world around them by using sensors. Working with sensor data for perception is a core element of robotics. Here you'll work with 3D point cloud data to perform segmentation tasks using techniques like RANSAC and clustering.

  3D PERCEPTION

• Introduction to Term 2

  In this course, you’ll get an introduction to Term 2, and explore hardware commonly used in robotics. You’ll learn the uses of common sensors, and which ROS packages you need to support them. Those students with NVIDIA Jetson TX2 Developer Kit hardware will learn how to set up the system and interact with external hardware.

• Robotic Systems Deployment

  In this course, you’ll learn new tools, and the embedded workflow as you move from code on a host system to code on a target system. You’ll work through a familiar problem with these new tools, then extend what you’ve learned in a project.

  ROBOTIC INFERENCE

• Localization

  Learn how Gaussian filters can be used to estimate noisy sensor readings, and how to estimate a robot’s pose relative to a known map of the environment with Monte Carlo Localization (MCL).

  WHERE AM I?

• SLAM

  Learn how to create a Simultaneous Localization and Mapping (SLAM) implementation with ROS packages and C++. You’ll achieve this by combining mapping algorithms with what you learned in the localization lessons.

  MAP MY WORLD ROBOT

• Reinforcement Learning for Robotics

  Begin by learning how to build a basic end-to-end reinforcement learning agent, termed a deep Q-network (DQN). Then, enhance it to create a more complex agent that can pick and place from visual input.

  PICK AND PLACE WITH DEEP LEARNING

• Path Planning and Navigation

  Extend your RL Engine with more advanced techniques for navigation, and compare these with classic approaches. Finally, combine SLAM and navigation into a single comprehensive project!

  HOME SERVICE ROBOT