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