What we’re about
A group for experienced and aspiring data professionals.
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Upcoming events
7
•OnlineFrom Biotechnology to Bioinformatics Software
OnlineDeveloping tools to make complex biological data more accessible – with Sebastian Ayala Ruano
Sebastian Ayala Ruano began his studies in Biotechnology Engineering, but soon realized the wet lab wasn’t the right environment for him. With a growing interest in programming, he pursued a minor in Software Engineering and later a Master’s degree that connected both fields.
Today, Sebastian works in bioinformatics software development, contributing to open-source projects like MicW2Graph, VueGen, and VueCore. These tools help researchers make sense of complex multi-omics data, supporting new ways of understanding biology.
We plan to cover:
- Transitioning from biotechnology to computational work
- Building and maintaining open-source bioinformatics tools
- The challenges and opportunities of multi-omics data analysis
- Advice for life science students interested in programming and bioinformatics
About the GuestSebastian Ayala Ruano is a bioinformatics software developer whose work bridges biotechnology and computational biology. He has contributed to open-source tools including MicW2Graph, VueGen, and VueCore, designed to simplify multi-omics data analysis for researchers. Previously, he worked on projects in cheminformatics, peptide discovery, and network-based analysis, and has developed educational bioinformatics tools for open science communities.
Sebastian is currently a research assistant in the Multiomics Network Analytics Group at DTU Biosustain in Denmark, where he focuses on integrating machine learning and network science into biological research. Also, he is an active member of several research, open-science, and software development communities (The Turing Way, Open Life Science, Streamlit Creators, ISCBSC, and The Carpentries) and led initiatives that advance Bioinformatics in Ecuador and Latin America. He shares his projects and insights through his personal website and GitHub.
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27 attendees
•OnlineThe Future of AI Agents
OnlineExploring open source profitability and small language models – Aditya Gautam
Aditya Gautam has built his career at the intersection of AI research, large-scale deployment, and public discourse. With experience at Google, Meta, and leading academic conferences, he works on large language models, AI agents, and responsible AI at scale.
In this episode, Aditya explores the debates around open-source AI, the economics behind LLMs, and the barriers enterprises face when adopting AI agents. He also shares his perspective on the rise of small language models and what these shifts mean for the future of AI.
We plan to cover:
- Open-source AI: democratization and risks
- The economics of LLMs and the challenge of profitability
- Why enterprises struggle to adopt AI agents in practice
- The role of small language models in efficiency and cost reduction
- Emerging trends in AI research and deployment
About the Guest
Aditya Gautam is an AI researcher and engineer whose work spans industrial innovation, academic research, and AI policy. He has held roles at Google and Meta, working on recommendation systems, integrity, and large-scale generative AI deployment. His research covers topics including misinformation, multi-agent systems, and LLM evaluation, and he has published in top-tier conferences such as ICWSM while serving as a peer reviewer for venues like NeurIPS, ICML, and AAAI.
Aditya is also an active voice in the AI community: he speaks at industry events such as the Databricks Data + AI Summit and Analytics Vidhya, contributes to policy discussions around regulations like the EU Digital Services Act, and shares insights on the economics and practical adoption of LLMs and AI agents. He holds a Master’s degree from Carnegie Mellon University.
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38 attendees
•OnlineDeploying ML Models with Kubernetes
OnlineA hands-on introduction to serving machine learning models in production - Alexey Grigorev
This is the third workshop in our ML series on ML model deployment.
Building on the FastAPI service created in Part 1, we’ll now show how to deploy that service using Kubernetes, the industry standard for managing containerized applications in production.
Led by Alexey Grigorev, this workshop focuses on infrastructure, orchestration, and scaling.What You'll Learn
- How to containerize a model and preprocessing step as microservices
- How to use Docker Compose to test your setup locally
- How to deploy your services to Kubernetes
- How to connect everything together into a working ML system
- The basics of using EKS (Elastic Kubernetes Service) for managed deployments
It will be a live demo with practical tips and a chance to ask your questions. This workshop gives you a real feel for how ML models are deployed in real-world environments.
Thinking About ML Zoomcamp?
This workshop reflects the updated content of Module 5 in the ML Zoomcamp, giving you a taste of modern ML deployment practices you'll explore in the course.ML Zoomcamp is our free 4-month course that takes you from beginner to advanced ML engineer. It covers the fundamentals of ML, from regression and classification to deployment and deep learning.
The new cohort of the ML Zoomcamp starts on September 15, 2025. You can join it by registering here.
About the SpeakerAlexey Grigorev is the Founder of DataTalks.Club and creator of the Zoomcamp series.
Alexey is a seasoned software and ML engineer with over 10 years in engineering and 6+ years in machine learning. He has deployed large-scale ML systems at companies like OLX Group and Simplaex, authored several technical books including Machine Learning Bookcamp, and is a Kaggle Master with a 1st place finish in the NIPS'17 Criteo Challenge.
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81 attendees
Past events
342
