Complete Intelligent Robotics, AI, Automation & RPA Course

Step into the world of intelligent automation with this comprehensive course designed to help you master modern robotics, Artificial Intelligence (AI), Robot Operating System (ROS & ROS2), and Robotic Process Automation (RPA). Whether you are a student, engineer, researcher, automation professional, or robotics enthusiast, this course provides the knowledge and practical understanding required to build intelligent robotic and automation systems for Industry 4.0.

You will begin by learning the foundations of intelligent robotics, including industrial robots, smart automation systems, robot sensors, perception, sensor fusion, computer vision, collaborative robots (cobots), Industrial IoT, and digital twins. Next, you will explore the core robotics algorithms that enable autonomous robots to perceive, localize, map, navigate, and make intelligent decisions. Topics include localization, occupancy grid mapping, SLAM, path planning, motion planning, obstacle avoidance, task planning, multi-robot coordination, and swarm intelligence.

The course then introduces Artificial Intelligence for robotics, covering machine learning, deep learning, convolutional neural networks (CNNs), object detection, reinforcement learning, predictive maintenance, edge AI, and AI-driven human–robot interaction. You will also gain practical knowledge of enterprise automation through Robotic Process Automation (RPA), including workflow automation, OCR, intelligent document processing, process mining, cognitive automation, hyperautomation, and AI-enabled RPA.

A separate section, that covers important MATLAB-based simulations of mobile robot localization, path planning, and trajectory planning algorithms, enabling learners to visually understand robot localization, movement, path generation, obstacle avoidance, and navigation from start to goal.

One of the highlights of this course is the dedicated section on real-world industrial case studies. You will analyze complete end-to-end workflows, including:

• Warehouse Robot Localization using Monte Carlo Localization (MCL/AMCL).

• Autonomous Navigation using the A* Path Planning algorithm.

• Factory Mapping using Simultaneous Localization and Mapping (SLAM).

• Vision-Guided Robotic Pick-and-Place Systems using computer vision, pose estimation, inverse kinematics, and motion planning.

• AI-Based Visual Quality Inspection using computer vision and deep learning techniques.

• Human–Robot Collaboration for safe and intelligent interaction in smart manufacturing environments.

• Intelligent Invoice Processing using Robotic Process Automation (RPA), OCR, AI document understanding, and ERP integration

These industrial case studies demonstrate how robotics, ROS & ROS2, AI, computer vision, robotics algorithms, and intelligent automation technologies work together to solve real-world industrial challenges through complete end-to-end workflows

By the end of this course, you will understand the technologies, algorithms, and intelligent automation techniques powering modern manufacturing, logistics, healthcare, warehouses, and smart factories. You will be equipped with the practical knowledge needed to design, analyze, and implement intelligent robotic and automation solutions for today's Industry 4.0 environments.