The goal of this group is to help you navigate the complex and rapidly evolving world of data science and artificial intelligence. This is your hub to stay up-to-date on the latest trends, learn specialized skills to turn raw data into valuable insights, connect with a community of like-minded individuals, and ultimately, become a Data Alchemist. Together, let's decode the language of data and shape a future where knowledge and community illuminate our way. Rules - Don't sell anything here or use Data Alchemy as any kind of funnel - We delete low effort community posts, and posts with poor English. Proofread your post first. - Help us make the posts high quality. If you see a low quality post, then click on the 3 dots on the post and "Report To Admins". Start by checking out these links - Classroom - Introduction - Roadmap - Contribution Be Aware of Scammers - Please be aware that this is a public group. Unfortunately, some people abuse the Skool platform to send DMs or post comments to trick people. This is the internet, so always do your own due diligence. Never automatically trust someone here on the Skool platform other than @Dave Ebbelaar's official account. To kick things off, please comment below, introducing yourself. Let us know: 1. Your name and where you're from 2. What project(s) you're currently focused on See you in the comments!

Anthropic has published a very interesting article about building AI agents. Have you read it? Anthropic engineers suggest that you should understand the underlying code before using any abstraction frameworks like LangGraph; otherwise, it may get hard for you to debug and understand your own code. Also, they suggest that you should only add complexity when it's really necessary for your use case. Simplicity is the best, and you shouldn't build agents when you don't need them. They also provided a detailed overview of commonly used agentic systems. Have a look at it 👉 https://www.anthropic.com/engineering/building-effective-agents

Hi, I am currently looking into how to leverage AI for our business processes in marketing. We are a small data & analytics company. I have some self-taught JavaScript experience, have experimented with n8n, and have done a lot of research on RAG. In my current state of thinking, I believe I first need a stronger foundation in Python and how it can be used for AI workflows and app development. But at the same time, I want to learn hands-on. I came across this community and find the concept very intriguing. So I wanted to ask those who took the courses how their experience compares to other courses?

Hey everyone, I just completed a new course for you: "Data Science Accelerator". This course will be unlocked, together with "Building Applications with LLMs" at level 3. How to level up? Just interact with the group, get likes and comments, and watch your level go up!

I've spent the last year watching something interesting happen in our field... Everyone's talking about GenAI. Every tweet, every product launch, every investor memo. But here's what's really happening: When you zoom in on the AI systems actually running in production today, almost none of them are GenAI. They're still powered by traditional ML — logistic regression, XGBoost, neural nets. But that won't last. I predict those numbers will completely flip over the next decade. GenAI is going to eat everything. But honestly, most developers aren't ready for that shift. Not because they aren't good - but because GenAI is evolving faster than any tech wave we've ever seen. There's no real roadmap. No clean, proven path to go from "I can prompt ChatGPT" to "I build production-ready GenAI systems." I've felt this gap myself. Even with a strong background in AI, I had to dig for answers, hack things together, and experiment like crazy to keep up. And when I started hiring engineers at Datalumina, I realized there's no proper training program for this new wave of AI engineering. So I built one. It started as an internal roadmap. Then I shared it within our community. The response? "This is exactly what I needed!" So now, it's official: The GenAI Accelerator is open for enrollment. ✓ A 6-week cohort-based program ✓ Built for developers who want to level up fast ✓ Focused on real, production-grade systems — not playground projects ✓ Based on 10+ years of building AI systems ✓ First cohort starts May 5th You'll learn techniques that aren't shared on YouTube or Medium. These are the same approaches used by big tech companies, but their employees can't openly share them online due to confidentiality agreements. But I don't care about competition. The AI market is growing exponentially. There's more than enough opportunity for every skilled developer. At Datalumina, we can't even take on 1% of the project requests coming our way. The demand for AI engineers is so massive that I'm not worried about "giving away secrets" - I'm focused on helping more developers build the skills needed to meet this demand.