About the course

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Learn the role of the Transformer architecture in modern AI systems

Learn how the Transformer architecture revolutionized modern artificial intelligence by enabling models to process and understand language more efficiently than previous approaches. This section explores how Transformers use attention mechanisms to capture context and relationships within data, making them highly effective for tasks like translation, text generation, and question answering. You will gain insight into why this architecture powers leading models such as GPT and BERT, and how it has become the foundation of today’s most advanced AI systems.

Explore popular models like GPT and BERT

Explore widely used language models such as GPT and BERT to understand their design, strengths, and real-world applications. This section compares how GPT focuses on generating coherent text and conversations, while BERT excels at understanding context and meaning within language. You will learn how these models are trained, what tasks they perform best, and how they have shaped modern natural language processing systems used in search engines, chatbots, and AI-powered tools.

Build simple applications powered by LLM APIs

Learn how to build simple, real-world applications using APIs from models like GPT. This section guides you through integrating LLM capabilities into your own projects, such as chatbots, content generators, or task automation tools. You will understand how to send prompts, handle responses, and structure inputs effectively to get reliable outputs. In addition, you will explore practical concepts like API authentication, rate limits, and cost management, along with basic techniques such as prompt design and response validation. By the end, you’ll be able to create and deploy lightweight applications that leverage LLMs to solve everyday problems efficiently.

Curriculum

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    Instructions for this course

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