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!

Recently I got into the world of development of applications for a personal business, the thing is that I'm quite good with the backend but I am a complete rookie in front end and development of graphic interfaces. I wondered what would recommend me to develop interfaces, preferably something I can use with Python and be multiplatform. I have been testing some Python libraries to create interfaces, but in general they make the interface look like a software of the 90s or very simple, I would like something that would allow me to create more beautiful interfaces, regardless of learning difficulty. I would like to read your recommendations in the comments 💬.

NVIDIA AgentIQ is an open-source library for connecting, evaluating, and accelerating teams of AI agents. The AgentIQ toolkit simplifies development while optimizing and increasing the accuracy of full-stack, complex agentic AI systems. https://developer.nvidia.com/agentiq

Naval Ravikant, co-founder of AngelList and well respected entrepreneur and investor, thinks that we are heading towards a future where we will all be freelancers again. He offers valuable insights into why this shift might occur Factors such as the rise of remote work, the emergence of freelance platforms, advancements in AI technology, and evolving cultural norms are all contributing to the gradual transformation of the work landscape, working together to reduce external transaction costs. Naval also makes a fair point about humans not being built to work consistently all the time and still be expected to remain productive. Quality of work output is not linear. He describes how the "modern knowledge worker athlete" is most productive. Which involves training hard, sprinting, resting, and reassessing, then using the feedback loop to prepare for the next sprint. Similar to how freelancers move from project to project. If you purely look at the numbers, Naval might be onto something here. According to a recent study by Upwork: - Freelancers made a significant contribution of $1.27 trillion to the U.S. economy in annual earnings in 2023, which is a substantial increase from $713 billion in 2014. - The study also revealed that the number of professionals freelancing has risen to nearly 64 million Americans, accounting for 38% of the U.S. workforce. This marks a noticeable growth from 34% in 2014. I've been freelancing for a decade, so I might be a bit biased, but I agree with Naval's perspective on the future of work. What do you think? Will the number of freelancers continue to increase in the future? And have you ever considered freelancing? What's holding you back? Let me know your thoughts in the comments below!

The course consists of 10 lessons that cover the fundamentals of building AI agents. Each lesson stands alone, so start wherever you like! ✨ [Link to the course in comments!] Here's what it covers: 🏁 Intro to AI Agents 🔍 Agentic Frameworks 🧠 Agentic Design Patterns 🔨 Tool Use Design Pattern 🔗 Agentic RAG 🛡️ Building Trustworthy AI Agents 🗺️ Planning Design Pattern 🤝 Multi-Agent Design Pattern 💭 Metacognition Design Pattern 🚀 AI Agents in Production