In this technical lecture, we will introduce the Gazebo/PyBullet robotic simulation framework, a valuable tool for simulating and testing robotic systems. Gazebo, an open-source robotics simulator, provides a realistic and customisable platform for simulating complex robotic scenarios. We will provide an overview of its key features, including the physics engine, sensor models, and support for various robotic platforms. PyBullet, a Python-based physics simulation engine, will also be discussed briefly. This simulator enables seamless interaction with machine learning frameworks used in robotics. Participants will gain a basic understanding of how Gazebo/PyBullet can be used to set up simulations, design robotic models, and simulate environments. Throughout the lecture, we will emphasise the potential benefits of using simulation in robotics research and development. We will highlight how Gazebo/PyBullet can assist in accelerating the development process, reducing costs, and mitigating risks associated with hardware testing. By the end of the lecture, attendees will have a general understanding of the Gazebo/PyBullet framework and its potential applications in robotic simulations. They will be encouraged to explore the framework further on their own, allowing them to delve deeper into its features and capabilities according to their specific needs.