EITC/AI/ADL Advanced Deep Learning

by EITCA Academy / Sunday, 07 February 2021 / Published in

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EITC/AI/ADL Advanced Deep Learning is the European IT Certification programme on Google DeepMind’s approach to advanced deep learning for artificial intelligence.

The curriculum of the EITC/AI/ADL Advanced Deep Learning focuses on theoretical aspects and practical skills in advanced deep learning techniques from the perspective of Google DeepMind organized within the following structure, encompassing comprehensive and structured EITCI certification curriculum self-learning materials supported by referenced open-access video didactic content as a basis for preparation towards earning this EITC Certification by passing a corresponding examination.

Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. Deep learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields including computer vision, machine vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance.

Artificial neural networks (ANNs) were inspired by information processing and distributed communication nodes in biological systems. The adjective “deep” in deep learning refers to the use of multiple layers in the network. Early work showed that a linear perceptron cannot be a universal classifier, and then that a network with a nonpolynomial activation function with one hidden layer of unbounded width can on the other hand so be. Deep learning is a modern variation which is concerned with an unbounded number of layers of bounded size, which permits practical application and optimized implementation, while retaining theoretical universality under mild conditions. In deep learning the layers are also permitted to be heterogeneous and to deviate widely from biologically informed connectionist models, for the sake of efficiency, trainability and understandability, whence the “structured” part.

To acquaint yourself in-detail with the certification curriculum you can expand and analyze the table below.

The EITC/AI/ADL Advanced Deep Learning Certification Curriculum references open-access didactic materials in a video form. Learning process is divided into a step-by-step structure (programmes -> lessons -> topics) covering relevant curriculum parts. Participants can access answers and ask more relevant questions in the Questions and answers section of the e-learning interface under currently progressed EITC programme curriculum topic. Direct and unlimited consultancy with domain experts is also accessible via the platform integrated online messaging system, as well as through the contact form.
For details on the Certification procedure check How it Works.

Download the complete offline self-learning preparatory materials for the EITC/AI/ADL Advanced Deep Learning programme in a PDF file
EITC/AI/ADL preparatory materials – standard version
EITC/AI/ADL preparatory materials – extended version with review questions