#49 Why Become an LLM Developer?

Author(s): Towards AI Editorial Team

Originally published on Towards AI.

Good morning, AI enthusiasts! This week, I am super excited to finally announce that we released our first independent industry-focus course: From Beginner to Advanced LLM Developer. Put a dozen experts (frustrated ex-PhDs, graduates, and industry) and a year of dedicated work, and you get the most practical and in-depth LLM Developer course out there (~90 lessons). It is a one-stop conversion for software developers, machine learning engineers, data scientists, or AI/Computer Science students. Check the course here!

As I quit my PhD to build practical solutions, I realized there’s a massive discrepancy between academia and the industry, and it’s even worse in the LLM era. So we’ve gathered everything we worked on building products and AI systems and put them into one super practical industry-focused course. Right now, this means working with Python, OpenAI, Perplexity, LlamaIndex, Gradio, and many other amazing tools.

Even though the course is super practical (oriented towards building a real-world project), we believe the course teaches concepts that will stay relevant for a long time even as LLMs get better, such as reducing hallucinations, teaching how to work and use them, some cool theory and tips and more.

The only skill required for the book is some Python (or programming) knowledge.

We cover the full stack of learning to build on top of foundation LLMs — from choosing a suitable LLM application to collecting data, iterating on many advanced techniques (RAG, fine-tuning, agents), integrating industry expertise, and deploying. Students will create a working product, which we certify, and we also provide students instructor support in our Discord channel.

Find all the information directly on our course page!

— Louis-François Bouchard, Towards AI Co-founder & Head of Community

Learn AI Together Community section!

AI poll of the week!

I was quite surprised to see the poll results; the trend had been moving towards skill-based learning, and LLMs also accelerated that. So, for those who said yes, I’m quite curious to know why. Share it in the thread, let’s chat!

Collaboration Opportunities

The Learn AI Together Discord community is flooding with collaboration opportunities. If you are excited to dive into applied AI, want a study partner, or even want to find a partner for your passion project, join the collaboration channel! Keep an eye on this section, too — we share cool opportunities every week!

1. Wildgamingyt is looking for AI developers for a project. If you enjoy building AI chatbots or want to try it, reach out in the thread!

2. Akeshav writes a newsletter on Substack and needs help with research and data visualization. If you have some time to spare and want to work on something like this, connect in the thread!

Meme of the week!

Meme shared by rucha8062

TAI Curated section

Article of the week

Unlocking Key Technologies in Document Parsing By Florian June

This article provides a comprehensive overview of document parsing technologies, covering both modular pipeline systems and end-to-end approaches using large vision-language models. It explores key aspects like layout analysis, OCR, mathematical expression recognition, table detection and recognition, and chart processing. It highlights popular open-source tools and evaluates their performance for text and table extraction. While modular systems are currently widely used, end-to-end models show potential for future advancements. It also discusses challenges and future directions, emphasizing the need for diverse datasets, improved interpretability, and feedback loops to enhance model performance and address complex document types.

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Published via Towards AI