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applications, including search engines, chatbots, and text classification systems. It will also present and refresh the relevant deep learning architectures on which recent LLM architectures capitalise
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architectures, diffusion models, and autoregressive techniques, as well as their applications in natural language processing, computer vision, and beyond. The course emphasizes hands-on learning, enabling
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. The ideal candidate will provide expert instruction on neural network architectures, backpropagation, activation functions, and optimization algorithms, ensuring students gain practical skills using
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Engineering, Computer Science, Computer Engineering, Information Systems, or a closely related field. Technical Expertise in one or more of the following areas: Software architecture and design patterns