Short Summary
A beginner-friendly course that explains how generative AI and large language models (LLMs) work, using simple language and practical examples. Learn what is happening behind the scenes, what to trust, what to double-check, and how to choose the right approach for real tasks.
About This Course
AI tools are everywhere, but most people only see the chat box. This course helps you understand what is actually happening so you can use these tools with better judgment. You will learn the core ideas behind LLMs, tokens, context windows, training vs usage, why models make mistakes, and how systems like RAG and fine-tuning differ.
The goal is not to turn you into a researcher. The goal is to help you make smarter decisions: which tool to use, how to reduce errors, how to protect data, and how to explain AI outputs inside a team or organisation. By understanding the fundamentals of generative AI, you will be able to navigate the rapidly evolving landscape of AI tools and technologies with confidence.
For instance, you will learn how to evaluate the strengths and weaknesses of different LLMs, such as their ability to handle nuanced language, common biases, and domain-specific terminology. You will also discover how to design effective prompts that elicit accurate and relevant responses from AI models, and how to identify potential pitfalls and limitations of AI-generated content.
Key Concepts Covered
The course covers a range of essential topics, including the basics of LLMs, such as tokens, embedding, and self-attention mechanisms. You will also learn about context windows, which determine how much text an LLM can consider when generating a response, and how this affects the model’s performance. Additionally, you will explore the differences between training and usage, and how these phases impact the accuracy and reliability of AI outputs.
Furthermore, you will delve into the world of RAG (Retrieval-Augmented Generation) and fine-tuning, which are advanced techniques used to improve the performance and adaptability of LLMs. By understanding these concepts, you will be able to appreciate the complexities and challenges involved in developing and deploying AI models, and make more informed decisions about their application in real-world scenarios.
Practical Applications and Benefits
The course is designed to be highly practical, with numerous examples and case studies that illustrate the benefits and challenges of using generative AI in various contexts. You will learn how to apply AI tools to tasks such as content generation, language translation, and text summarization, and how to evaluate the results to ensure they meet your needs and expectations.
By taking this course, you will gain a deeper understanding of the capabilities and limitations of generative AI, and develop the skills and knowledge needed to harness its potential in your work or personal projects. Whether you are a business professional, a content creator, or simply an AI enthusiast, this course will provide you with a solid foundation for exploring the exciting and rapidly evolving world of generative AI.
