{"id":53960,"date":"2025-06-03T11:42:03","date_gmt":"2025-06-03T11:42:03","guid":{"rendered":"https:\/\/academy.xebia.com\/us\/?post_type=course&p=53960"},"modified":"2025-09-22T17:05:38","modified_gmt":"2025-09-22T17:05:38","slug":"deep-learning-and-ai-in-one-day","status":"publish","type":"course","link":"https:\/\/academy.xebia.com\/us\/training\/deep-learning-and-ai-in-one-day\/","title":{"rendered":"Deep Learning and AI in One Day"},"content":{"rendered":"\n
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\n\t\t\t\t\n\tDeep Learning and AI in One Day<\/h1>\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n\t
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\n\tEveryone talks AI, but what is it exactly? This 1-day course will take you on a journey to demystify AI. You will learn the fundamentals of Deep Learning and neural networks which form the basis of all modern AI models, how they work, how they differ from traditional Machine Learning, what are common challenges in building AI applications, and how you can get started building, training and fine-tuning AI models yourself.

At the end of this training, you will understand the inner working of AI but also its limitations, which can help you make better decisions whether its building your own AI systems or implementing and adapting out-of-the-box solutions.
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\n\t\t\n\tLooking to upskill your team or organization?<\/h2>

\n\tBrijesh will gladly help you further with custom training solutions for your organization. <\/p>

\n\t\t\n\n\t\n\t\n\t\n<\/picture>\t\t\n\tBrijesh Kohli
Training Advisor<\/h2>\t\t

\n\t+1 (404) 988-3790<\/a>
Brijesh.kohli@xebia.com<\/a><\/a>
https:\/\/www.linkedin.com\/in\/brijesh-kohli\/<\/a><\/a><\/p>\t<\/div>\n\t\n\t\t\tGet in touch<\/span>\n\t\n\t<\/a>\t<\/div>\n<\/div>\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n\t\t<\/div>\n\t<\/div>\n\n\t<\/div>\n<\/div>\t\t<\/div>\n\t<\/div>\n\n\n\n

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\n\tAfter the training, you will be able to:<\/p>\t

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\n\tUnderstand how Deep Learning & AI work as the basis of all modern AI systems<\/p><\/div>\n\n\n\n

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\n\tUtilize and build upon existing \u201cfoundational\u201d models using Hugging Face\u2019s vast model library<\/p><\/div>\n\n\n\n

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\n\tDifferentiate between classical machine learning and modern deep-learned AI, including when which models are preferred<\/p><\/div>\n\n\n\n

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\n\tUnderstand which challenges exist in building deep neural networks and what countermeasures are taken architecturally and by careful hyperparameter tuning<\/p><\/div>\n\n\n\n

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\n\tEffectively communicate the mechanisms, capabilities and limitations of modern deep learned AI systems to non-technical stakeholders<\/p><\/div>\n\n\n\n

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\n\tBuild your own dense neural networks using Tensorflow\/Keras<\/p><\/div>\n\n\t<\/div>\n<\/div>\n\t\t<\/div>\n\t<\/div>\n\n<\/div>\n\n<\/div>\n\t\t<\/div>\n\t<\/div>\n\n\n\n

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