Ai Fundamentals Courseware
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AI Fundamentals Courseware
Author: Reinier van den Biggelaar
language: en
Publisher: Van Haren
Release Date: 2023-09-26
The AI Fundamentals courseware offers an AI training course designed for professionals in business or government environments who want to understand the benefits and applications of AI in their work environment. This course covers topics such as data management for AI, building and assessing AI applications, ethics and trustworthiness, and organizational success factors for enabling humans and machines to work together. The course addresses key questions such as “Where does Data Management end and AI application begin?” from a management perspective. Subjects covered include the applications and benefits of AI, data and robots, predictions and algorithms, machine and deep learning, building and reviewing AI applications, data management for AI, ethics and trustworthiness, organizational success factors for helping humans and machines work together, and the future of AI. This courseware educates for three certifications within it’s three-day combined program. It’s also possible to cut the material in pieces for a module teaching approach. The EXIN BCS Artificial Intelligence Essentials, testing the fundamental concepts of AI. This AI for Business and Government certification (the AI Brevet) which was established by the Netherlands AI Coalition (NL AIC) as a standard for professionals who want to use Artificial Intelligence. EXIN BCS Artificial Intelligence Foundation, which has a more IT-technical perspective.
AI Fundamentals Courseware
Author: Van Haren Publishing
language: en
Publisher: Van Haren Publishing
Release Date: 2024-05-29
'The AI Fundamentals courseware offers an AI training course designed for professionals in business or government environments who want to understand the benefits and applications of AI in their work environment. This course covers topics such as data management for AI, building and assessing AI applications, ethics and trustworthiness, and organizational success factors for enabling humans and machines to work together. The course addresses key questions such as "Where does Data Management end and AI application begin?" from a management perspective. Subjects covered include the applications and benefits of AI, data and robots, predictions and algorithms, machine and deep learning, building and reviewing AI applications, data management for AI, ethics and trustworthiness, organizational success factors for helping humans and machines work together, and the future of AI. This courseware educates for three certifications within it's three-day combined program. It's also possible to cut the material in pieces for a module teaching approach. -The EXIN BCS Artificial Intelligence Essentials, testing the fundamental concepts of AI. -This AI for Business and Government certification (the AI Brevet) which was established by the Netherlands AI Coalition (NL AIC) as a standard for professionals who want to use Artificial Intelligence. -EXIN BCS Artificial Intelligence Foundation, which has a more IT-technical perspective.
Deep Learning for Coders with fastai and PyTorch
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala