Welcome to an exciting 10-week journey into the world of large language models!
LLMs are currently experiencing a substantial surge in popularity. Their significance has notably increased in diverse applications, including natural language processing, machine translation, and code and text generation. This rise in prominence is driven by a growing trend among both companies and individuals to leverage LLMs for automating a wide range of tasks. Understanding and learning about LLMs is highly valuable in light of their growing usage and transformative impact across various domains.
If you're eager to dive into this trend, you'll discover plenty of resources on the internet. But here's the catch – many of them are all over the place, missing a step-by-step guide from basics to real-world use. This can be overwhelming, and you might feel a bit lost.
Imagine this course as your comprehensive guide, exploring every aspect of using LLMs in real-world scenarios. It serves as the crucial link that brings everything together. Each week, we'll delve into the above topics, providing in-depth insights and hands-on experiences. This approach ensures you gain a thorough and well-rounded understanding of every facet within the topic.
We've organized the content into four key pillars –
- Fundamentals (Week 1)
- Tools and Techniques (Weeks 2-5)
- Deployment and Evaluation (Weeks 6-9)
- Challenges and Future trends (Weeks 9-10)
This course caters to a diverse audience, including business leaders, professionals, computer science enthusiasts, or students looking to enhance their knowledge in LLMs. While we aim to keep mathematical foundations relatively light, we'll touch on LLM architectural basics in week 11 as bonus content for those interested in delving into LLM research.
To make this course accessible to a wide audience, we've designed it as a self-paced audit course. You can register for the course here and course material will be released weekly, featuring mind maps, "ETMI5: Explain to Me in 5" sections for a quick overview, relevant resources, and comprehensive content to ensure your understanding of each topic. Additionally, we'll provide research papers and distilled summaries to keep you updated on the latest research. This page serves as your central hub for all resources.
Stay informed by registering for email notifications whenever new content is uploaded, or follow our updates on LinkedIn. For any queries, feel free to contact the instructor at [email protected] or on LinkedIn. At the end of each week, we'll address frequently asked questions. To maximize your learning experience, allocate 2-3 hours weekly for reading content and engaging in suggested hands-on experiments.
- Understanding the practical fundamentals of LLMs, including its capabilities and limitations
- Hands-on experience with end-to-end execution of LLM use cases
- Learning best practices for exploring and evaluating the usefulness of LLMs in specific scenarios
- Proficiency in integrating and comprehending new updates in LLMs, effectively fitting each piece into the larger puzzle and understanding its relevance.
This course content is developed by Aishwarya Naresh Reganti. The course is offered independently, for free and is not affiliated with her professional responsibilities or employer. The content presented in this course is intended for educational purposes only and does not reflect the views or policies of any associated organizations.
To cite this guide, use the below format:
@article{areganti_generative_ai_guide,
author = {Reganti, Aishwarya},
journal = {https://github.com/aishwaryanr/awesome-generative-ai-resources},
month = {01},
title = {{Generative AI Guide}},
year = {2024}
}
[MIT License]