Mastering Generative AI: Model Foundations and NLP

This intermediate-level IBM course equips you with highly sought-after skills in generative AI and natural language processing (NLP) that are driving the AI revolution. With the generative AI market projected to grow 42% annually by 2033, this course positions you at the forefront of an expanding field. You'll learn to implement, train, and evaluate generative AI models for NLP applications like text generation, summarization, translation, and conversational interactions. The curriculum covers essential techniques including document classification, language modeling, and language translation while developing a fundamental understanding of both small and large language models. You'll master methods to convert words to features through one-hot encoding, bag-of-words, embedding, and embedding bags, and implement PyTorch to embed models using word2vec for text data representation. Through hands-on labs, you'll build neural networks for document categorization, explore N-gram language models and sequence-to-sequence models, and evaluate generated text using metrics like BLEU. The practical experience gained implementing document classification with torchtext, training simple language models, and integrating pre-trained embedding models provides job-ready skills that will help you stand out as an AI professional.