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Completed coursework for DataTalksClub's LLM Zoomcamp 2026, covering the core building blocks of production RAG/LLM systems: Agentic RAG (converting OpenAI-based notebooks to Groq API), Vector Search with sentence-transformers and minsearch, Orchestration with Kestra (workflow automation in a containerized environment), and Retrieval/LLM Evaluation using Hit Rate and MRR metrics across text, vector, and hybrid search approaches. Debugged real-world integration issues including API compatibility, deprecated model migrations, and credential rotation.
GitHub :https://github.com/BimbsyStats/llm-zoomcamp-2026
https://github.com/BimbsyStats/llm-zoomcamp-hw5
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Hi everyone!
I'm new here, so I wanted to introduce myself.
I learned the basics of Python about two years ago, and a year ago I started a degree in AI and Data Science. I'm currently in my third semester, and I'm focused on developing my programming and data skills while building my first real-world experience.
For now, I'm looking to contribute to smaller tasks such as data cleaning, data analysis, automation, and logical scripting. I don't expect to jump directly into complex projects; my goal is to help with the work I can handle while learning how software and data projects actually work in the industry.
I'm also very interested in how AI fits into programming. In my personal projects, I try to use AI primarily as a learning and reasoning tool rather than as a replacement for understanding or writing the code myself. I like using it more as a Socratic teacher: asking questions, challenging my reasoning, explaining concepts, and helping me find mistakes.
At the same time, I recognize that AI is becoming almost indispensable in modern development. But I believe that understanding the fundamentals is just as important. I want to learn how things work, not simply how to get an AI to produce them.
Currently, I'm working on a physics simulator as a personal project. It's still a work in progress, but I hope to share my progress here in the future.
I'm here to learn, contribute, and get a better understanding of what working in the industry is actually like. If there are small tasks where I can be useful while continuing to learn, I'd be happy to help.
Best regards!
Here is a professional English translation of your post that captures the exact same message and tone:
Just wrapped up the project, and I realized this is definitely the picture worth sharing the most! 😁
Sometimes people look at the final dashboard and think that’s where all the work happens, but the real magic starts right here... the Data Model.
Behind every single relationship here is a lot of thinking, testing, and tweaking until everything finally clicked into place.
Alhamdulillah, the project is officially complete, and I’ve learned way more from it than I initially expected.
Any feedback is more than welcome! 🙏
#PowerBI #DataAnalytics #PowerBIDeveloper #Portfolio #OpenToWork
Built an AI-powered Log Analyzer using Python and FastAPI to automate log analysis and troubleshooting. The system processes application/system logs, performs rule-based analysis, and uses an LLM to identify problems, root causes, severity, possible causes, and recommended actions. Exposed the functionality through REST APIs with structured Pydantic responses for reliable and consistent results.
Tech: Python, FastAPI, LLM/Ollama, Pydantic, REST APIs, Log Parsing, Prompt Engineering, Git.
