Intermediate Python. If you know the basics of Python and feel comfortable with it, you’re almost there! If not, check out these links:

1. Python tutorial in the official documentation
2. LearnPython website with interactive tutorials

3. Introduction to Computer Science and Programming in Python, an MIT course published as video lectures with supporting materials.

Jupyter Notebooks. Familiarity with the notebooks enables you to combine notes and code and store the results from code execution (output images). It only takes about half an hour to get the hang of the Jupyter environment. Check out the installation instructions and the official documentation.

Linux Command Line (bash terminal)., If you know how to enter simple bash commands inside the Jupyter environment you’re ready. To round out your knowledge, check out this command line tutorial.

Deep-learning layers and convolutional neural network (CNN-based) architectures. To complete the certification, we’re assuming you know the basics of deep learning, and if not, here’s an overview to get your started. As you progress, You should become familiar with layers such as dense, convolution, pooling, and recurrent. We’re using the SqueezeNet, ssd-mobilenet, and generative adversarial network (GAN) architectures.

OpenCV. OpenCV is a real-time computer vision library. Before the training, you should know how to load an image or video, and how to resize, convert color space, and do simple processing. If you haven’t used OpenCV before, check out these first four tutorials.

OpenVINO™ Toolkit. The Intel® Edge AI Certification program will rely heavily on this toolkit for deep learning inferencing, optimization, and deployment of your AI models. We recommend downloading and familiarizing yourself ahead of time to make getting started easier.

1. Learn more: Overview of OpenVINO™ toolkit

2. Download the toolkit here: OpenVINO™ toolkit