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Learning to harness the power of photogrammetry requires a solid foundation in computer vision and 3D geometry. To get started, one must first grasp the fundamental concepts behind structure from motion (SfM) algorithms, which enable computers to reconstruct 3D models from 2D images. This involves understanding how cameras capture scenes, as well as the mathematical principles governing the process of triangulating points between multiple viewpoints. With a strong grasp of these basics, one can move on to more advanced topics such as feature detection and matching, bundle adjustment, and finally, texture mapping. The ability to accurately estimate camera poses and 3D structures is essential for photogrammetry applications ranging from surveying and mapping to film production and architecture visualization.