Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course introduces Large Language Models (LLMs) and equips you to leverage them for generative AI, content creation, and practical business applications. You'll gain a clear understanding of LLM architecture, machine learning fundamentals, neural networks, embeddings, and model fine-tuning techniques. The course emphasizes hands-on exercises to ensure you can apply these concepts in real-world scenarios. The journey begins with a historical overview of Artificial Intelligence, illustrating the evolution of AI to modern LLMs. You’ll explore machine learning, deep learning, and transformer architectures that power GPT models, building a strong foundation for understanding how LLMs function. Core concepts like neural networks and embeddings are explained with practical examples, preparing you to harness these models effectively. Next, the course delves into generative AI applications. You will learn prompt engineering, using ChatGPT for content creation, and methods to refine outputs for diverse tasks. Templates and guided exercises help structure content while highlighting the importance of human ethical judgment. You’ll also examine popular LLMs, model scaling, and advanced research insights, ensuring you can select and optimize models for specific projects. This course is designed for AI enthusiasts, machine learning professionals, and anyone keen to use LLMs in real-world applications. No prior AI experience is required. By the end, learners will be confident applying LLMs for content, translation, and AI-driven projects while making ethically informed decisions. The course difficulty is beginner-friendly but builds toward advanced practical skills.

Syllabus

Introduction

In this module, we will explore the basics of Artificial Intelligence and Large Language Models (LLMs), providing you with a solid foundation. You will learn the history of AI, its growth, and the role LLMs play within the field. This section also offers resources and prompt packs to help you get started with practical LLM applications.

LLM Architecture

In this module, we will dive deep into the technical aspects of LLMs, starting with machine learning, the backbone of AI. You will also learn about the core components of LLMs, such as GPTs, Transformers, and neural networks. Additionally, we will cover key concepts like embeddings and fine-tuning, helping you understand the architecture that powers LLMs.

LLMs for Generative AI

In this module, we will focus on the practical use of LLMs in generative AI. You will discover how to harness the power of tools like ChatGPT, refine your prompts, and improve content generation. This section will also help you make ethical decisions when working with LLMs and choose the right model for your specific needs.