Mastering Gen AI: LLM Architecture & Data Preparation
This course provides practical competencies in generative artificial intelligence, large language models, and natural language processing data management, all underpinned by a credential esteemed within the industry.
Description for Mastering Gen AI: LLM Architecture & Data Preparation
Understanding Generative AI Architectures: Examine generative AI models and their corresponding architectures, encompassing Recurrent Neural Networks (RNNs), transformers, Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and diffusion models.
Applying Large Language Models (LLMs): Gain insights into the application of LLMs, including GPT, BERT, BART, and T5, in various language processing tasks.
Tokenization Techniques in Natural Language Processing: Acquire proficiency in the implementation of tokenization for the preprocessing of unrefined textual data utilizing Natural Language Processing libraries, including NLTK, spaCy, BertTokenizer, and XLNetTokenizer.
Constructing NLP Data Loaders with PyTorch: Acquire the expertise necessary to develop NLP data loaders utilizing PyTorch for the processes of tokenization, numericalization, and padding of textual data.
Level: Intermediate
Certification Degree: yes
Languages the Course is Available: 1
Offered by: On edX provided by IBM
Duration: 2�3 hours per week 2 weeks (approximately)
Schedule: Flexible
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