**Leveraging Simulation Expertise for Rapid Prototyping, Automation, and Scalable Data Pipelines - Orell Garten**

​**Description:**

​Join us for an in-depth conversation with Orell Garten, a former simulation engineer turned freelance data consultant. He’ll share how his background in high-precision electromagnetic simulations led to today’s rapid-prototyping, automation, and production-grade data pipelines.

​What we’ll cover:

* ​**Simulation Foundations:** How simulations inform the way Orell builds reliable data pipelines.
* ​**Rapid MVPs:** The one-month prototype rule and how to apply it in your work.
* ​**Production Checklist:** The must-do steps (CI/CD, monitoring, schema versioning) and the common blind spots teams miss.
* ​**Workflow Automation:** Orell’s quick rule for spotting repeatable tasks, measuring ROI, and a real example of saved engineering hours.

​Orell’s disciplined, practical approach will give you clear, actionable steps to move from concept to production. **Register now and bring your questions!**
​
About the Speaker:
​
**Orell Garten** is a freelance IT consultant and software engineer based in Leipzig, Germany. He began his career building high-precision simulation pipelines at TU Dresden and Ruhr-Universität Bochum. After pausing his PhD when COVID hit, he joined a government-backed startup program to validate research prototypes in the market.
​

**Join our slack: https://datatalks.club/slack.html**

Berlin DataTalksClub Group

Events Datatalks.Club

Feras Shamasna

Tomo Lewandowski

Yulia Vilensky

Varshith Anilkumar

Ameen siddiqui

Rashmi Kamath

Anastasiia 

Adrian Nastase (sql-troubles)

Yusuf Raheem

Christoph Lindemann

Miko

Justyna Wojtczak

Polina

Serge

Bernhard S

Artur Siekielski

Federico

Jerome Roeser

From Simulation Algorithms to Production-Grade Data Systems

Online event

In this hands-on workshop, we'll walk through building a knowledge graph from REST API documentation using dlt and Cognee. Rather than treating APIs as flat data sources, we'll model their underlying concepts—resources, relationships, endpoints, and behaviors—as a structured graph of interconnected nodes.

​Using dlt, we'll extract and transform documentation from multiple REST APIs into structured representations. These are then embedded into a shared semantic space using Cognee, where a central ontology node anchors all inputs—linking method definitions, OpenAPI specs, and DLT-specific constructs across APIs.

​We'll explore:

* ​How to extract and normalize API docs into semantic node sets
* ​How to build and extend a central ontology that connects multiple API sources
* ​How to visualize and query the resulting knowledge graph to answer conceptual questions.

​By the end of the session, you'll know how to construct and query a multi-source, semantically-indexed knowledge graph, enabling richer understanding of complex API ecosystems.

​About the speaker:

​Hiba Jamal
​**Hiba** is an AI Engineer at dltHub. She works with data pipelines, data modelling, LLMs, and ML tasks in her current role. Before that, she has worked at other startups in data roles.
​
​​This event is sponsored by [dlthub.](https://dlthub.com/)
​
​​​​​[DataTalks.Club](http://datatalks.club/) is the place to talk about data. [Join our slack community](https://datatalks.club/slack.html)!

Jaikumar S

Vlad-Emil Petrea

Paras

Daniel Rios

Abila Annamalai

nemehalrababeh

shweta lamkhade

Praewpun Chaiyapornruangdet

Christos Golsouzidis

Moussa Ndour

Ali Musab

Adam Vajda

finn sandø

Michael R.

Purushothaman Srikanth

Anastasiia Kulakova

Abdallah AGUERZAME

From REST to reasoning: ingest, index, and query with dlt and Cognee

**A hands-on workshop on turning retrieval-augmented generation into agentic AI flows - Alexey Grigorev**

​**Description:**
​Retrieval-Augmented Generation (RAG) is a common approach for building AI assistants, but most implementations stop at a single search + answer pattern. In this practical workshop, we go a step further.

​You'll learn how to make RAG pipelines more agentic: enabling decision-making, tool use, multi-step reasoning, and real-time interaction with users. We’ll build step by step, from simple retrieval to agent-powered assistants capable of asking follow-up questions, running tool calls, and updating their own knowledge base.

​What we’ll cover:

* ​Build a basic RAG pipeline: Implement search + prompt + LLM logic using course FAQs
* ​Add agentic behavior
\- ​Let the assistant decide when to search or answer
\- ​Introduce state\, reasoning\, and multi\-step flows
* ​Implement agentic search
\- Iterate over multiple search queries
\- Use search history and reasoning to refine results
* ​Use OpenAI function calling
\- Add tool support: search and FAQ updates
\- Maintain interaction history and responses
* ​Build a working assistant
\- Organize your logic with chat_assistant\.py
\- Interact with a live\, modular AI assistant
* ​Explore PydanticAI
\- Define tools with type hints and docstrings
\- Run your assistant in a fully typed agent framework

​What you’ll get:
​A working RAG-based AI assistant that can:

* ​Search FAQs
* ​Decide when to act
* ​Ask follow-up questions
* ​Add entries to its own knowledge base

​Everything runs in Jupyter with Python. You can follow along with GitHub Codespaces or use your own environment.
​
About the Speaker:
​**Alexey Grigorev** is the creator of DataTalks.Club and instructor of the popular Zoomcamp series. He designs and teaches practical AI/ML workflows used by thousands of learners globally. In this workshop, Alexey brings his hands-on teaching style to the emerging field of agentic LLMs, helping you build useful assistants from scratch.

​
**Join our slack: https://datatalks.club/slack.html**

Johan Dettmar

Adriana Istrate

Eugene

eduardo.fuentevilla

Helen S

Aman Khan

Vlad

Tony Barratt

Dario

Matthias Prellwitz

Nilufar Hosseini

Richard Meinsen

Matias Villaverde

From RAG to Agents: Making Smart AI Assistants (LLM Zoomcamp bonus module)

​**Using Zen Principles to Bridge Technical Excellence and Strategic Outcomes - Lior Barak**

​Despite 97% of organizations investing in data, only 24% of executives feel truly data-driven. Too often, data teams build impressive pipelines and dashboards that never connect back to business results.
​In this podcast episode, Lior Barak, Data Zen Master and author of Data Is Like Hummus, shares how **ancient Zen principles**, paired with **modern data strategy frameworks**, can help teams close the gap between technical effort and business impact.

​What we plan to cover:

* ​**The Data Strategy Triangle:** How to balance maintenance, innovation, and rollout, and align your work with long-term organizational goals.
* ​**Executive KPIs that Matter:** The two metrics every data team should track to tie technical output to revenue growth, cost reduction, or retention.
* ​**Wabi-Sabi for Data Products:** How embracing imperfection and transparency builds trust faster than chasing unattainable “perfect” data.
* ​**The Data Team Stress Index:** A tool to prioritize work, anticipate burnout, and make strategic decisions about tooling and staffing as your team grows.

​About the speaker:

​**Lior Barak** is an independent data strategy consultant and former hands-on practitioner. He’s helped organizations in tech, finance, and healthcare evolve from reactive firefighting to sustainable, high-impact data practices.

​He’s also the creator of:

* ​**The Data Ecosystem Vision Board**: a visual planning tool for aligning data efforts across teams
* ​**The Data Product Lifecycle Manager**: a framework for tracking ROI across a data product’s entire lifespan

​
Lior also writes *Cooking Data*, a newsletter that pairs mindful data strategy with nourishing, practical advice. As he says: “**Data is like hummus: it should be simple and nourishing.**”

**Join our slack: https://datatalks.club/slack.html**​

Serhii Basetskyi

Olaf

Max Kashirin

Zoraida

Torsten

Egidija Valaityte

Gautam

EvaSchreyer

Tanvi

Melek Ergin

Micha Y

Mindful Data Strategy: From Pipelines to Business Impact

Get a taste of the upcoming **AI Dev Tools Zoomcamp** in this free, hands-on workshop led by course creator **Alexey Grigorev**.

## ​What to expect?

​In this hands-on session, we'll introduce you to the concepts of vibe coding and co-coding, and show you how to build a simple game like "Match Three" using AI.
![User Uploaded Image](https://images.lumacdn.com/cdn-cgi/image/format=auto,fit=cover,dpr=2,quality=75,width=800,height=533.3333333333334/editor-images/tk/4b1d66f5-f422-401a-be9d-b7e42fec4765.png)
​You’ll see what it's like to co-code with AI in real time, just like we'll do in the **[AI Dev Tools Zoomcamp](https://github.com/DataTalksClub/ai-dev-tools-zoomcamp)**.

​You'll learn:

* ​What "vibe coding" is and how AI-assisted development works
* ​Which AI tools are available for developers today
* ​How to quickly start a new project using AI support
* ​How to build game UI and logic inside Cursor
* ​The kinds of projects and skills you'll explore in the full course
* ​How AI can speed up and streamline your development process

​Expect a lively, interactive session where you can ask questions, follow along, and see the value of AI in your coding workflow.

> ​Whether you’re already signed up or still thinking about joining, this is a great way to see how the course works in practice.

## ​

## Curious about the full Zoomcamp?

​We'll give you a rundown of the kinds of projects and skills you'll tackle, and show you how AI can make your dev flow more efficient.

***

## ​About the speaker

​Alexey Grigorev is the founder of [DataTalks.Club](https://datatalks.club/), a community of 73,000+ data enthusiasts.
​

​​​**​​​[DataTalks.Club](http://datatalks.club/) is the place to talk about data. [Join our slack community](https://datatalks.club/slack.html)!**

Emmanuel Opoku

Samuel

Dmitry P

Baki Bektas

Tosh

Marcelo Carvalho Fernandes

Ewa Wileczek

Vladyslav Mosiichuk

Carlos Biagolini

Frank Merwerth 

Elif Sema Şanal

Donald

Mohd Hasan

Yacine Touati

Nada

Introduction to Vibe Coding: Build a Game with AI

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