Robotics Engineering

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About Course

Step into the exciting world of Robotics Engineering and master the skills to design, build, and program intelligent machines! This course takes you from fundamentals to advanced robotics, covering mechanical design, electronics, embedded systems, AI, and automation. You’ll learn how to create autonomous robots, leverage computer vision and machine learning, and integrate IoT and cloud robotics. Whether you want to work in industrial automation, humanoid robotics, or start your own robotics business, this course equips you with the expertise to innovate and lead in the robotics revolution. Enroll now and start building the future.

What Will You Learn?

  • Fundamentals of Robotics
  • Mechanical & Electronics Design
  • Programming for Robotics
  • Computer Vision & AI in Robotics
  • Autonomous Navigation & Path Planning
  • Industrial & Humanoid Robotics
  • IoT & Cloud Robotics
  • Monetizing Robotics Skills
  • Capstone Project & Career Development

Course Content

Introduction to Robotics
This module provides a foundational understanding of robotics, exploring its history, evolution, and real-world applications across industries such as manufacturing, healthcare, space exploration, and automation. Students will learn about the core components of robots, including mechanical structures, sensors, actuators, and control systems. The module also introduces key concepts in mechatronics, ethics in robotics, and future trends, setting the stage for deeper exploration into robotic engineering.

  • History & Evolution of Robotics
  • Applications of Robotics in Various Industries
  • Fundamentals of Mechatronics
  • Ethics & Future Trends in Robotics

Mechanical Design for Robotics
This module explores the core principles of designing robotic systems, focusing on kinematics, dynamics, and structural integrity. Students will learn about robotic joints, linkages, actuators, and mechanisms essential for motion control. The course also covers material selection, CAD modeling, and 3D printing for prototyping robot components. By the end of this module, students will have the skills to design, analyze, and optimize robotic structures for various applications.

Electronics & Embedded Systems for Robotics
This module introduces the electronic components and embedded systems that power robotic devices. Students will learn about microcontrollers, sensors, actuators, circuit design, and power management essential for robotic functionality. The course covers Arduino, Raspberry Pi, and real-time operating systems (RTOS), along with signal processing and communication protocols. By the end of this module, students will be able to integrate hardware and software to build intelligent and autonomous robotic systems.

Programming for Robotics
This module focuses on the software and programming techniques essential for controlling robotic systems. Students will learn to program robots using Python, C++, and ROS (Robot Operating System) while exploring key concepts such as motion control, sensor integration, and real-time decision-making. The course covers algorithm development, kinematics, and automation scripting, enabling students to build and program autonomous and interactive robots. By the end of this module, students will have hands-on experience in coding intelligent robotic behaviors.

Robot Perception & Computer Vision
This module explores how robots sense, interpret, and understand their environment using computer vision and sensor technologies. Students will learn about image processing, object detection, depth sensing, and pattern recognition using tools like OpenCV, LiDAR, and machine learning models. The course also covers sensor fusion techniques for combining data from cameras, IMUs, and other perception systems. By the end of this module, students will be able to develop vision-based robotics applications for autonomous navigation, object tracking, and real-world interaction.

Artificial Intelligence & Machine Learning in Robotics
This module explores how AI and machine learning empower robots to learn, adapt, and make intelligent decisions. Students will learn about neural networks, reinforcement learning, deep learning, and probabilistic models for robotic applications. The course covers path planning, autonomous decision-making, and real-time AI-driven control systems using frameworks like TensorFlow and PyTorch. By the end of this module, students will be able to develop AI-powered robotic systems capable of autonomous navigation, object recognition, and adaptive problem-solving.

Autonomous Robotics & Path Planning
This module focuses on the principles and algorithms that enable robots to navigate and operate independently in dynamic environments. Students will learn about simultaneous localization and mapping (SLAM), path planning algorithms (A, Dijkstra, RRT), obstacle avoidance, and motion control*. The course covers sensor fusion, GPS-based navigation, and real-time decision-making for autonomous mobile robots and self-driving systems. By the end of this module, students will be able to design and implement intelligent robotic navigation systems for various real-world applications.

Humanoid & Industrial Robotics
This module explores the design, control, and application of humanoid and industrial robots in real-world settings. Students will learn about biomechanics, kinematics, and artificial intelligence used in humanoid robots, along with robotic arms, automation, and precision control systems for industrial robots. The course covers actuators, motion planning, and collaborative robotics (cobots) used in manufacturing, healthcare, and service industries. By the end of this module, students will understand how to develop and program robots for human-like interactions and industrial automation.

Internet of Things (IoT) & Cloud Robotics
This module explores how IoT and cloud computing enhance robotic capabilities by enabling remote control, data sharing, and real-time processing. Students will learn about IoT sensors, edge computing, MQTT protocols, and cloud-based AI integration for robotics. The course covers robot-to-robot (R2R) and robot-to-cloud (R2C) communication, allowing robots to operate collaboratively over networks. By the end of this module, students will be able to develop smart, connected robots with cloud-based intelligence and automation.

Monetizing Robotics Skills & Real-World Impact
This module explores practical ways to apply robotics knowledge for financial growth, career advancement, and societal impact. Students will learn about entrepreneurship in robotics, freelancing, consulting, and launching robotics startups. The course covers robotics applications in industries like healthcare, manufacturing, and automation, as well as grant opportunities, competitions, and funding sources. By the end of this module, students will understand how to turn their robotics expertise into profitable ventures and create innovative solutions for real-world problems.

Capstone Project & Career Readiness
This module serves as the culmination of the Robotics Engineering course, where students apply their knowledge to develop a real-world robotics project. Students will work on designing, programming, and deploying a functional robotic system while incorporating concepts from previous modules. The course also includes career guidance, resume building, interview preparation, and networking opportunities to help students transition into the industry. By the end of this module, students will have a portfolio-ready robotics project and the skills needed to pursue careers, internships, or entrepreneurial ventures in robotics.

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