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In this Introduction to Large Language Models course, you’ll learn how these advanced AI systems understand and generate human-like language. Businesses rely on them for creating content and automating customer support, making them a key part of AI-driven solutions.
You’ll start by exploring what LLMs are and how they function in AI-driven applications. The course covers their evolution from early rule-based models to the advanced transformer-based systems in modern AI. You’ll also learn how self-attention, encoding, and decoding processes help LLMs to analyze and generate language effectively. Finally, you’ll discover the training process behind LLMs and how they can be optimized and fine-tuned to deliver accurate responses.
By the end of this course, you’ll have a strong foundation in LLMs, allowing you to understand their role in AI. You’ll also learn how businesses use them to drive innovation.
You'll learn what Large Language Models are and how they function in AI-driven applications, their evolution from rule-based to transformer-based systems, how self-attention, encoding, and decoding work, and how LLMs are trained, optimized, and fine-tuned to deliver accurate responses.
It suits anyone who wants a strong foundation in LLMs to understand their role in AI and how businesses use them to drive innovation.
The course develops skills in Large Language Modeling, Machine Learning Model Training, and Natural Language Processing.
Lessons cover an introduction, defining LLMs and their technical concepts and significance, the historical evolution of LLMs, the core transformer architecture, training processes and data requirements, and a knowledge test.
Businesses rely on LLMs for creating content and automating customer support, making them a key part of AI-driven solutions.