Mastering Generative AI: Model Foundations and NLP

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The gen AI market is projected to grow by 42% CAGR by 2033 (Bloomberg). With natural language processing being key to this gen AI revolution, skilled data scientists and AI professionals are in high demand!

If you’re aiming to break into the AI field, this IBM course on Generative AI - Model Foundations and NLP equips you with the skills employers crave.

Learn how AI professionals use NLP for tasks like text generation, summarization, translation, and conversational interactions.

This course will guide you to implement, train, and evaluate gen AI models for NLP.

You'll delve into document classification, language modeling, language translation, and learn to build both small and large language models.

Gain expertise in converting words into features with techniques like one-hot encoding, bag-of-words, embedding, and embedding bags. Learn to use PyTorch for embedding models using word2vec for text data representation.

Develop, train, and optimize neural networks for document categorization, explore N-gram language models, sequence-to-sequence models, and assess generated text quality with BLEU metrics.

Experience hands-on labs to implement document classification with torchtext in PyTorch.

Build and train a simple language model using a neural network to generate text, and integrate pre-trained models like word2vec for text analysis and classification.

If you're aspiring to be an AI professional or data scientist and want to enhance your resume with sought-after gen AI skills, ENROLL TODAY and elevate your career!

Prerequisites:

Basic knowledge of Python and familiarity with machine learning and neural network concepts is recommended.

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