All Episodes
DataTalks.Club — 222 episodes
Engineering Your Own AI Assistant - Paul Iusztin
Thriving in the AI Era with Human Skills - Maryam Ramezani-Bartsch
Building a Career in AI From Real Estate to AI Engineering - Gustaf Gyllensporre
How to Build AI that actually Ships in Production - Aleksandr Kim
AI Adoption in Enterprise Beyond Writing Code - Ivan Bilan
Applied AI 2026 Berlin Conference Interview
From GenAI Pilots to Production - Nikita Kozodoi
From Notebook to Production: Building End-to-End AI Systems - Mariano Semelman
Data Makers Fest 2026 Conference Interviews
Competitions: Beyond the Kaggle Leaderboard - Tatiana Habruseva
PyConDE 2026 Conference Interviews
Starting a Data Conference: The Data Makers Fest Story - Leonid Kholkine
Understanding the AI Engineer Role - Nasser Qadri
Data Engineer Career in 2026: Roles, Specializations, and What Companies Look for - Slawomir Tulski
Inside the AI Engineer Role: Tools, Skills, and Career Path - Ruslan Shchuchkin
How to Become an AI Engineer After a Career Break - Revathy Ramalingam
The Future of AI Agents - Aditya Gautam
Foundations of Analytics Engineer Role: Skills, Scope, and Modern Practices - Juan Manuel Perafan
AI Engineering: Skill Stack, Agents, LLMOps, and How to Ship AI Products - Paul Iusztin
Applying ML: An Ongoing Personal Journey
Building Pet Health Tech: ML, Sensors, and Dog Behavior Data
From Full-Time Mom to Head of Data and Cloud - Xia He-Bleinagel
From Black-Box Systems to Augmented Decision-Making - Anusha Akkina
Qdrant 2025 Conference Interviews
How to Build and Evaluate AI systems in the Age of LLMs - Hugo Bowne-Anderson
From Biotechnology to Bioinformatics Software - Sebastian Ayala Ruano
Lessons from Applied AI: Tesla, Waymo, and Beyond - Aishwarya Jadhav
Building reliable AI products in the era of Gen AI and Agents - Ranjitha Kulkarni
From Theme Parks to Tesla: Building Data Products That Work
From Semiconductors to Machine Learning: A Career in Data and Teaching
Lessons from Two Decades of AI - Micheal Lanham
Berlin PyData 2025 Conference Interviews
From Astronomy to Applied ML - Daniel Egbo
Berlin Buzzwords 2025 Conference Interviews
From Medicine to Machine Learning: How Public Learning Turned into a Career - Pastor Soto
How to Rebuild Data Trust? Mindful Data Strategy and Maintenance vs Innovation - Lior Barak
From Simulations to Freelance Data Engineering: Orell's Journey Out of Academia and Into Consulting - Orell Garten
Can You Quit Your Job and Still Succeed as a Data Freelancer?
From Hackathons to Developer Advocacy - Will Russel
Build a Strong Career in Data - Lavanya Gupta
From Supply Chain Management to Digital Warehousing and FinOps - Eddy Zulkifly
Data Intensive AI - Bartosz Mikulski
MLOps in Corporations and Startups - Nemanja Radojkovic
Trends in Data Engineering – Adrian Brudaru
Competitive Machine Leaning And Teaching – Alexander Guschin
Redefining AI Infrastructure: Open-Source, Chips, and the Future Beyond Kubernetes – Andrey Cheptsov
Linguistics and Fairness - Tamara Atanasoska
Career choices, transitions and promotions in and out of tech - Agita Jaunzeme
Career advice, learning, and featuring women in ML and AI - Isabella Bicalho
AI in Industry: Trust, Return on Investment and Future - Maria Sukhareva
Large Hadron Collider and Mentorship – Anastasia Karavdina
MLOps as a Team - Raphaël Hoogvliets
Using Data to Create Liveable Cities - Rachel Lim
DataTalks.Club 4th Anniversary AMA Podcast – Alexey Grigorev and Johanna Bayer
Human-Centered AI for Disordered Speech Recognition - Katarzyna Foremniak
DataOps, Observability, and The Cure for Data Team Blues - Christopher Bergh
Working as a Core Developer in the Scikit-Learn Universe - Guillaume Lemaître
Building a Domestic Risk Assessment Tool - Sabina Firtala
Berlin Buzzwords 2024
Community Building and Teaching in AI & Tech - Erum Afzal
Working in Open Source - Probabl.ai and sklearn - Vincent Warmerdam
AI for Ecology, Biodiversity, and Conservation - Tanya Berger-Wolf
Knowledge Graphs and LLMs Across Academia and Industry - Anahita Pakiman
Inclusive Data Leadership Coaching - Tereza Iofciu
Building Production Search Systems - Daniel Svonava
Building Machine Learning Products - Reem Mahmoud
Make an Impact Through Volunteering Open Source Work - Sara EL-ATEIF
Accelerating The Job Hunt for The Perfect Job in Tech - Sarah Mestiri
Machine Learning Engineering in Finance - Nemanja Radojkovic
Stock Market Analysis with Python and Machine Learning - Ivan Brigida
Bayesian Modeling and Probabilistic Programming - Rob Zinkov
Navigating Challenges and Innovations in Search Technologies - Atita Arora
The Entrepreneurship Journey: From Freelancing to Starting a Company - Adrian Brudaru
Become a Data Freelancer - Dimitri Visnadi
AI for Digital Health - Maria Bruckert
Cracking the Code: Machine Learning Made Understandable - Christoph Molnar
The Unwritten Rules for Success in Machine Learning - Jack Blandin
From a Research Scientist at Amazon to a Machine learning/AI Consultant - Verena Webber
From Marketing to Product Owner in Search - Lera Kaimashnіkova
Collaborative Data Science in Business - Ioannis Mesionis
Bridging Data Science and Healthcare - Eleni Stamatelou
DataTalks.Club Anniversary Interview - Alexey Grigorev, Johanna Bayer
Data Engineering for Fraud Prevention - Angela Ramirez
From Data Manager to Data Architect - Loïc Magnien
Pragmatic and Standardized MLOps - Maria Vechtomova
Democratizing Causality - Aleksander Molak
Mastering Data Engineering as a Remote Worker - José María Sánchez Salas
The Good, the Bad and the Ugly of GPT - Sandra Kublik
LLMs for Everyone - Meryem Arik
Investing in Open-Source Data Tools - Bela Wiertz
Why Machine Learning Design is Broken - Valerii Babushkin
Interpretable AI and ML - Polina Mosolova
From Scratch to Success: Building an MLOps Team and ML Platform - Simon Stiebellehner
From MLOps to DataOps - Santona Tuli
Data Developer Relations - Hugo Bowne-Anderson
Lessons Learned from Freelancing and Working in a Start-up - Antonis Stellas
Data Access Management - Bart Vandekerckhove
Data Strategy: Key Principles and Best Practices - Boyan Angelov
Practical Data Privacy - Katharine Jarmul
Building Scalable and Reliable Machine Learning Systems - Arseny Kravchenko
Building an Open-Source NLP Tool - Johannes Hötter
Navigating Industrial Data Challenges - Rosona Eldred
Mastering Self-Learning in Machine Learning - Aaisha Muhammad
The Secret Sauce of Data Science Management - Shir Meir Lador
SE4ML - Software Engineering for Machine Learning - Nadia Nahar
Starting a Consultancy in the Data Space - Aleksander Kruszelnicki
Biohacking for Data Scientists and ML Engineers - Ruslan Shchuchkin
Analytics for a Better World - Parvathy Krishnan
Accelerating the Adoption of AI through Diversity - Dânia Meira
Staff AI Engineer - Tatiana Gabruseva
The Journey of a Data Generalist: From Bioinformatics to Freelancing - Jekaterina Kokatjuhha
Navigating Career Changes in Machine Learning - Chris Szafranek
Preparing for a Data Science Interview - Luke Whipps
Indie Hacking - Pauline Clavelloux
Doing Software Engineering in Academia - Johanna Bayer
Data-Centric AI - Marysia Winkels
Business Skills for Data Professionals - Loris Marini
From Software Engineer to Data Science Manager - Sadat Anwar
Teaching and Mentoring in Data Analytics - Irina Brudaru
Technical Writing and Data Journalism - Angelica Lo Duca
From Digital Marketing to Analytics Engineering - Nikola Maksimovic
Product Owners in Data Science - Anna Hannemann
Building Data Science Practice - Andrey Shtylenko
Large-Scale Entity Resolution - Sonal Goyal
From Data Science to DataOps - Tomasz Hinc
Data Science Career Development - Katie Bauer
From Testing Phones to Managing NLP Projects - Alvaro Navas Peire
Responsible and Explainable AI - Supreet Kaur
Building Data Science Practice - Andrey Shtylenko
No episode this week
Leading Data Research - David Bader
Dataset Creation and Curation - Christiaan Swart
Data Mesh 101 - Zhamak Dehghani
Growing Data Engineering Team in a Scale-Up - Mehdi OUAZZA
Lessons Learned About Data & AI at Enterprises - Alexander Hendorf
MLOps Architect - Danny Leybzon
Decoding Data Science Job Descriptions - Tereza Iofciu
Data Science for Social Impact - Christine Cepelak
Hiring Data Science Talent - Olga Ivina
From Open-Source Maintainer to Founder - Will McGugan
Designing a Data Science Organization - Lisa Cohen
Developer Advocacy Engineer for Open-Source - Merve Noyan
Data Scientists at Work - Mısra Turp
Freelancing and Consulting with Data Engineering - Adrian Brudaru
Getting a Data Engineering Job (Summary and Q&A) - Jeff Katz
Using Data for Asteroid Mining - Daynan Crull
Machine Learning in Marketing - Juan Orduz
From Academia to Data Analytics and Engineering - Gloria Quiceno
Teaching Data Engineers - Jeff Katz
From Roasting Coffee to Backend Development - Jessica Greene
Recruiting Data Engineers - Nicolas Rassam
Storytime for DataOps - Christopher Bergh
Machine Learning and Personalization in Healthcare - Stefan Gudmundsson
Innovation and Design for Machine Learning - Liesbeth Dingemans
Hacking Your Data Career - Marijn Markus
Visualising Machine Learning - Meor Amer
From Math Teacher to Analytics Engineer - Juan Pablo
From Data Science to Data Engineering - Ellen König
Becoming a Data Engineering Manager - Rahul Jain
A/B Testing - Jakob Graff
Machine Learning System Design Interview - Valerii Babushkin
Career Coaching - Lindsay McQuade
Product Management Essentials for Data Professionals - Greg Coquillo
Recruiting Data Professionals - Alicja Notowska
DataTalks.Club Behind the Scenes - Eugene Yan, Alexey Grigorev
DTC's minis - From Data Engineering to MLOps - Sejal Vaidya
Becoming a Data Science Manager - Mariano Semelman
Leading NLP Teams - Ivan Bilan
Product Management for Machine Learning - Geo Jolly
Moving from Academia to Industry - CJ Jenkins
Advancing Big Data Analytics: Post-Doctoral Research - Eleni Tzirita Zacharatou
Becoming a Data Product Manager - Sara Menefee
Data Science Manager vs Data Science Expert - Barbara Sobkowiak
Ace Non-Technical Data Science Interviews - Nick Singh
Becoming a Solopreneur in Data - Noah Gift
Building Business Acumen for Data Professionals - Thom Ives
Conquering the Last Mile in Data - Caitlin Moorman
Similarities and Differences between ML and Analytics - Rishabh Bhargava
Building and Leading Data Teams - Tammy Liang
What Researchers and Engineers Can Learn from Each Other - Mihail Eric
Introducing Data Science in Startups - Marianna Diachuk
Defining Success: Metrics and KPIs - Adam Sroka
Making Sense of Data Engineering Acronyms and Buzzwords - Natalie Kwong
Mastering Algorithms and Data Structures - Marcello La Rocca
Chief Data Officer - Marco De Sa
Freelancing in Machine Learning - Mikio Braun
Launching a Startup: From Idea to First Hire - Carmine Paolino
Approach Learning as ML Project - Vladimir Finkelshtein [mini]
Humans in the Loop - Lina Weichbrodt
Running from Complexity - Ben Wilson
I Want to Build a Machine Learning Startup! - Elena Samuylova
Big Data Engineer vs Data Scientist - Roksolana Diachuk
Build Your Own Data Pipeline - Andreas Kretz
From Software Engineering to Machine Learning - Santiago Valdarrama
Analytics Engineer: New Role in a Data Team - Victoria Perez Mola
Data Governance - Jessi Ashdown, Uri Gilad
What Data Scientists Don’t Mention in Their LinkedIn Profiles - Yury Kashnitsky
Becoming a Data-led Professional - Arpit Choudhury
How to Market Yourself (without Being a Celebrity) - Shawn Swyx Wang
From Physics to Machine Learning - Tatiana Gabruseva
What I Learned After Interviewing 300 Data Scientists - Oleg Novikov
Effective Communication with Business for Data Professionals - Lior Barak
Data Observability - Barr Moses
Shifting Career from Analytics to Data Science - Andrada Olteanu
Transitioning from Project Management to Data Science - Ksenia Legostay
Building Online Tech Communities - Demetrios Brinkmann
DataOps 101 - Lars Albertsson
The Essentials of Public Speaking for Career in Data Science - Ben Taylor
New Roles and Key Skills to Monetize Machine Learning - Vin Vashishta
Personal Branding - Admond Lee Kin Lim
The ABC’s of Data Science - Danny Ma
Translating ML Predictions Into Better Real-World Results with Decision Optimization - Dan Becker
Feature Stores: Cutting through the Hype - Willem Pienaar
The Rise of MLOps - Theofilos Papapanagiotou
Getting Started with Open Source - Vincent Warmerdam
Developer Advocacy for Data Science - Elle O'Brien
The Importance of Writing in a Tech Career - Eugene Yan
Mentoring - Rahul Jain
Standing out as a Data Scientist - Luke Whipps
Building a Data Science Team - Dat Tran
Processes in a Data Science Project - Alexey Grigorev
Roles in a data team - Alexey Grigorev