What you'll learn
Understand the importance of large language models in natural language processing (NLP) and their role in production.
Gain familiarity with prominent large language models, such as GLaM, Megatron-Turing NLG, Gopher, Chinchilla, PaLM, OPT, and BLOOM, and learn the key insights f
Learn the basics of transfer learning and transformer training to optimize AI models in NLP applications.
Be able to articulate the advancements and key contributions of each large language model, from GPT-3 to present day

Requirements
Basic understanding of natural language processing (NLP) and familiarity with programming concepts is helpful, but not required.

Description
This course provides an overview into the world of generative artificial intelligence (AI) and the use of large language models. As a participant, you'll explore the key concepts, techniques, and best practices involved in working with large language models, which have become increasingly important in natural language processing (NLP).In this course, you'll gain a comprehensive understanding of large language models, their significance in natural language processing (NLP), and how to effectively use them in your AI projects. This course introduces you to the most prominent models, including GLaM, Megatron-Turing NLG, Gopher, Chinchilla, PaLM, OPT, and BLOOM, highlighting essential insights from each. You'll also learn about their practical applications in production and the importance of transfer learning and transformer training for optimizing your models. By the course's end, you'll have an updated understanding of advancements since the release of GPT-3 and the major contributions of these large language models.By the end of the course, you'll have a solid understanding of how to integrate large language models into your generative AI projects and the latest advancements in the field. Whether you're a data scientist, AI engineer, or software developer, this course will equip you with the skills and knowledge needed to leverage large language models for cutting-edge generative AI applications.

Who this course is for
Data scientist, AI engineer, or software developer,Anyone interested in AI

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