Fundamental Computer Science skills; Object-oriented programming basics; Experience in Swift or Objective-C. Familiarity with Xcode.
We do not provide a computer for the class. Please, make sure to bring your own computer with the latest version of Xcode already installed. You can download the latest version from the Mac AppStore or from the Apple Developer Website.
Our training days are typically eight hours long. Usually from 9am to 6pm with lunch provided. For each topic we are sure to be both informative and interactive. We cover the key concepts first and then complete exercises that engage what we have learned. We strive to make our training relevant and unique. Therefore we tailor each training classes to the needs of the students, creating variety from class to class.
For more information check our Frequently Asked Questions.
We are passionate about iOS applications and enjoy sharing this passion with others. Our training is designed for developers interested in using the latest technologies to create innovative cutting edge applications that enhance the user experience. All of our training material is written in house and consistently updated. We also offer follow up consulting to all our clients to ensure that the material learned in training is used effectively. Ultimately, our goal is to provide an unparalleled tight knit learning environment that allows our clients to continue to push iOS development further.
Digital Signal Processing with vDSP. Large vector manipulation with vecLib. BLAS. Image Processing with vImage. Importing from and exporting to Core Graphics. Core Video interoperability.
Capture images and video. Capture depth. Capture faces and machine readable codes with AVFoundation. Read and write a video file.
Fundamental components. GPU resources. GPU functions. GPU commands. Rendering pipeline and render commands. Vertex and fragment shaders.
Keras and TensorFlow
Neural networks. Convolutional Neural Networks. Recurrent Neural Networks. Introduction to Keras and TensorFlow.
Exporting Keras and TensorFlow models to CoreML. Integrating a CoreML model in an iOS app. Integrating custom layers in CoreML. CNN and CoreML. RNN and CoreML.
Metal Performance Shaders and Accelerate
Using Metal for image and video processing. Custom compute shaders. Using MPS for Image Processing and Matrix Operations.
Node graph. Geometries. Geometry sources and geometry elements. Materials. Lights. Physically-based Rendering. Animations in SceneKit. Metal custom shaders in SceneKit. Importing 3D objects using Model I/O.
ARSession and ARConfiguration. ARKit views. ARAnchor. ARCamera and ARFrame. World tracking with ARKit. Handling 3D interactions in ARKit. 3D face tracking. Light management.
GameplayKit and AI for video games
Decision trees. Path finding. Agents, Goals and Behaviors. Procedural Noise. Randomization. Rule systems.