​If you have a desktop full of saved tutorials, downloaded recordings, and PDF badges, but nothing live to show for it—you’re not building capability. You’re just collecting content. ​I had to face this truth myself: watching someone else build isn't learning. Real growth only happens when you put yourself through the actual cycle: ​Understand: Explain the concept in your own words with zero tabs open. If you can't, you don't actually get it yet. ​Apply: Build something real. Not a step-by-step tutorial clone, but something original where you have to break things and fix them yourself. ​Reflect: Look at what failed, what surprised you, and why it broke. ​Improve: Take real feedback, adjust the code, and make it better. ​Stop treating learning like a checklist of completed videos. Pick a real problem, build the solution, and share the raw process—not just the shiny certificate at the end. ​What’s one thing you’re building right now that’s forcing you past the "tutorial phase"? Drop it below 👇

I wanted to share a little about Nexa AI since it was one of the projects I worked on for the Agentic AI Demo Challenge by Decoding Data Science. The idea was to create an app that could help people who aren’t sure what they want to do next with their careers. Honestly, when I started, I wasn’t completely sure how I was going to turn the idea into an actual AI application. I just started building and figured things out as I went. I got to explore AI agents, work on the idea, make changes along the way, and learn from the whole process. And then somehow... Top 10 Finalist! 🎉 I also got my certificate for the challenge. Really glad I decided to give Nexa AI a try.

I completed my computer science diploma. I study Python and machine learning. Theory alone falls short. Real progress requires action. I earned my Certificate of Commitment and took the DDS Builder Codex Pledge. I commit to being a builder. My focus shifts to analyzing data and building predictive models. Thank you @Decoding Data Science for the support.

Launching into Builder Mode: Taking Action in My AI Journey. I’m excited to announce that I have completed AI Builder Codex and received my Certificate of Commitment from Decoding Data Science (DDS). To me personally, this achievement marks a transition into a new mindset. Instead of staying stagnant in just learning about AI, I’m looking to continue growing by building, experimenting, solving, and sharing what I learn along the way. AI Builder Codex helped provide me with a framework that I hope to implement throughout my learning journey: ✅ Identity — Identifying who you are as a technical professional and the standards you hold yourself to. ✅ Learn — Building skill with intention. Instead of learning what you can, learn how you can learn. ✅ Build — Creating tangible assets from your knowledge. Whether it’s new AI agents or using your knowledge to solve real world problems. ✅ Community — Share what you learn and build. Grow with others, learn from others, and find opportunities to collaborate. Moving forward, my philosophy will be simple: Learn → Build → Share → Elevate I believe that in order for someone to truly learn something, they must take action. Yes there is value in tutorials and online learning courses but what you really learn is by building projects, experimenting with new ideas, failing, and improving. Thank you to Mohammad Arshad, the Decoding Data Science team, and the entire DDS community for fostering a learning environment that values action, accountability, collaboration, and continual growth. This is just the launch pad. I cannot wait to build more projects, further my AI and automation knowledge, and continue transforming ideas into reality. 🚀 💬Let me know in the comments! What helped you transition from a learner to a builder? You can view my certificate here: https://lnkd.in/dMmVWAKy #DecodingDataScience #AIBuilders #ArtificialIntelligence #DDSBuilderCodex #TechBuilder #DataScience #BuildInPublic #DDSAmbassador

I just attended the “Agentic AI: From RAG to ReAct” Masterclass on AI agents by Decoding Data Science and this masterclass was Presented and wrapped up by Mohammad Arshad. I’ve been learning about and working with Artificial Intelligence, building AI agents, trying out automation, and working through a real-world use case throughout this journey. The real-world example was the Hala HR Chatbot, and learning about different AI systems and how certain LLM models can provide better responses to prompts than your average chatbot. My biggest takeaway was how we can build modern AI agents that can: ▶️Reasoning -Through various problems and know how to plan what actions to take. ▶️Tooling - Use tools, APIs, and other resources. ▶️Retrieve - Pull relevant information about the Hala HR Chatbot ▶️Connect- To databases and workflows ▶️Multi-Steps- Handle many multi-step tasks and know how to solve problems that require solutions. What I learned the most is to Think About. Problem → Use Case → Architecture → Prototype → Evaluation → Deployment. I loved this because most AI solution that we see out now are solving real problems not just using the latest shiny new tool. They check for a problem and build something that creates value. Also, learn how to analyze what they have built. I even got the chance to learn something today in the live session and correctly answered the questions that was provided. But since i joined the kahoot a little late. I got kicked off so I wasn’t able to get on the leader board 🎉. Thank you @decordingdatascience and Mohammad Arshad for allowing us to learn and experiment with these ideas in a hands-on way. Building, experimenting, and creating real-life solutions is how I learn. I’m excited to continue doing this on my journey. I’m looking forward to applying what I learned today and maybe even try to implement it into websites that I build in the future as i learn how to deploy these also being a beginner 🚀.