Generative AI isn’t just a faster “tool” for routine tasks—it becomes your creative “teammate” when you shift from issuing commands to engaging in a two-way dialogue of questions, feedback and iteration. By asking the model to first probe your goals, constraints and workflows, then coaching its drafts and supplying your unique “inspiration” (perspectives, examples and domain insights), you overcome human biases like satisfying and fixedness, unlock latent creative capacity, and discover novel applications you couldn’t predict. Treating AI as a collaborator rather than a mere answer engine is the key to accelerating innovation and achieving breakthrough results.

Being "good at data" won't be enough soon. The next wave of Data Alchemists will also be: - Great storytellers 📖 - Ethical decision-makers ⚖️ - Strategic thinkers ♟️ It’s not just about crunching numbers. It’s about making sense of the chaos, and leading the future. Your data skills + human skills = unstoppable. 🌟

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!

It’s easy to get lost in the algorithms, libraries, and fancy dashboards. But at its core, Data Science is about asking better questions. You can have the best model, but if you’re answering the wrong question, it’s useless. 🔥 A few underrated questions that lead to gold: - "What’s actually driving this behaviour?" - "What hidden assumptions are we making here?" - "If I could only track 3 metrics, what would they be?" The future isn’t about who builds bigger LLMS, but about who frames problems better than anyone else. Next time you dive into a dataset… pause. Ask yourself: Am I answering the right question?