DataTalks.Club
DataTalks.Club is a podcast about data science, analytics, and engineering. It features conversations with industry experts and practitioners, covering topics like machine learning, data engineering, and career development. The show aims to provide insights and practical advice for data professionals.
Episodes
From GenAI Pilots to Production - Nikita Kozodoi
In this talk, Nikita, Senior Applied Data Scientist at the AWS Generative AI Innovation Center, shares his expertise in bringing enterprise artificial intelligence out of the sandbox—from his early days optimizing traditional machine learning models like gradient boosting to deploying advanced production-grade GenAI pipelines. We explore what it really takes to move generative AI systems from pilo
From Notebook to Production: Building End-to-End AI Systems - Mariano Semelman
In this talk, Mariano, Lead Data Scientist and ML Engineer at OLX, shares his journey building high-impact AI media solutions. We explore the transition from traditional e-commerce models to Generative AI and Agentic tools, focusing on how to take AI products from a notebook to full-scale production.You’ll learn about:How to master the full product cycle from requirement gathering to deployment.Us
Data Makers Fest 2026 Conference Interviews
At Data Makers Fest, a recurring theme was the tension between GenAI hype and production reality. Speakers stressed that classical ML, MLOps, evaluation, data quality, and governance remain essential—especially in regulated sectors like fintech and healthcare. Another strong theme was inclusivity: building AI that serves smaller languages, diverse communities, and practitioners beyond the English-
Competitions: Beyond the Kaggle Leaderboard - Tatiana Habruseva
In this talk, Tatiana, Staff Software Engineer at LinkedIn, shares her journey from academic physics to becoming a Kaggle Master and winning the Sound Demixing Challenge. We explore how to use machine learning competitions as a strategic tool to build a high-impact career and bridge the gap between theory and production.You’ll learn about:Turning competition code into professional GitHub repos.Con
PyConDE 2026 Conference Interviews
At PyConDE 2026, community leaders, educators, and Python tooling builders explored how Python is evolving in the age of AI — and why human connection, mentorship, and strong fundamentals matter more than ever.Jessica Greene (Ecosia / PyLadies Berlin) spoke about her work as a machine learning engineer and community organizer. She highlighted PyLadies Berlin’s role in creating inclusive spaces for
Starting a Data Conference: The Data Makers Fest Story - Leonid Kholkine
In this talk, Leonid Kholkine, Head of Research & Development at Their Data and Co-founder of Data Makers Fest, shares his unique journey from leading international student organizations to building one of Europe’s premier data conferences. We explore the behind-the-scenes reality of community building, the evolution of the Portuguese data scene, and the technical challenges of managing AI obs
Understanding the AI Engineer Role - Nasser Qadri
In this talk, Nasser Qadri, AI Engineering Manager at Google, shares his unique career journey—from a PhD in Politics and International Relations to leading high-stakes AI initiatives. We explore the evolution of the AI Engineer role, the critical intersection of social science and machine learning, and how to build robust agentic workflows with engineering rigor.You’ll learn about:- Moving beyond
Data Engineer Career in 2026: Roles, Specializations, and What Companies Look for - Slawomir Tulski
In this talk, Slawomir Tulski, Data Leadership Consultant and former Meta Data Engineering Manager, shares his ten-year journey through the evolution of data systems—from researching glaciers in Poland to scaling the ads ranking infrastructure at one of the world's largest tech giants. We explore the shifting definition of the Data Engineer, the "Actionable Data" philosophy, and how
Inside the AI Engineer Role: Tools, Skills, and Career Path - Ruslan Shchuchkin
In this talk, Ruslan Shchuchkin, GenAI Engineer at Finance Guru, shares his unique career evolution from business administration and account management to building production-grade generative AI systems. We explore the transition from traditional Data Science to the modern AI Engineer role, defined by the "universal soldier" mindset and the ability to ship end-to-end products.You’ll lear
How to Become an AI Engineer After a Career Break - Revathy Ramalingam
In this episode Revathy Ramalingam, Senior Software Engineer and AI Engineer at a healthcare startup, shares her inspiring personal journey from over nine years in telecom software architecture to successfully transitioning back into the industry after a seven-year career break. We explore the evolution of the AI engineer role, the practical application of RAG pipelines, and the strategic use of A
The Future of AI Agents - Aditya Gautam
In this talk, Aditya, an experienced AI Researcher and Engineer, shares his technical evolution—from his roots in embedded systems to building complex, large-scale AI agent architectures. We explore the practical challenges of enterprise AI adoption, the shifting economics of LLMs, and the infrastructure required to deploy reliable multi-agent systems.You’ll learn about:- The ROI of Fine-Tuning: H
Foundations of Analytics Engineer Role: Skills, Scope, and Modern Practices - Juan Manuel Perafan
In this talk, Juan, Analytics Engineer and author of Fundamentals of Analytics Engineering share his professional journey from studying psychological research in Colombia to becoming one of the first analytics engineers in the Netherlands. We explore the evolution of the role, the shift toward engineering rigor in data modeling, and how the landscape of tools like dbt and Databricks is changing th
AI Engineering: Skill Stack, Agents, LLMOps, and How to Ship AI Products - Paul Iusztin
In this episode of DataTalks.Club, Paul Iusztin, founding AI engineer and author of the LLM Engineer’s Handbook, breaks down the transition from traditional software development to production-grade AI engineering. We explore the essential skill stack for 2026, the shift from "PoC purgatory" to shipping real products, and why the future of the field belongs to the full-stack generalist.Yo
Applying ML: An Ongoing Personal Journey
In this talk, Rileen, a Senior Computational Biologist and Cancer Data Scientist, shares his professional journey from physics and computer science to cutting-edge cancer genomics and applied machine learning. From his early work in alternative splicing models to deep learning in medical imaging, Rileen explains how biology, data science, and AI intersect to transform cancer research.TIMECODES:00:
Building Pet Health Tech: ML, Sensors, and Dog Behavior Data
In this session Sofya shares her journey building a pet-tech startup that blends machine learning sensor data and canine behavior analytics. She walks through her path from early programming explorations to launching a health monitoring device designed around anomaly detection and long-term behavioral baselines.TIMECODES: 00:00 Sofya's pet tech startup with machine learning sensor data and beh
From Full-Time Mom to Head of Data and Cloud - Xia He-Bleinagel
In this talk, Xia He-Bleinagel, Head of Data & Cloud at NOW GmbH, shares her remarkable journey from studying automotive engineering across Europe to leading modern data, cloud, and engineering teams in Germany.We dive into her transition from hands-on engineering to leadership, how she balanced family with career growth, and what it really takes to succeed in today’s cloud, data, and AI job m
From Black-Box Systems to Augmented Decision-Making - Anusha Akkina
In this talk, Anusha Akkina, co-founder of Auralytix, shares her journey from working as a Chartered Accountant and Auditor at Deloitte to building an AI-powered finance intelligence platform designed to augment, not replace, human decision-making. Together with host Alexey from DataTalks.Club, she explores how AI is transforming finance operations beyond spreadsheets—from tackling ERP limitations
Qdrant 2025 Conference Interviews
At Qdrant Conference, builders, researchers, and industry practitioners shared how vector search, retrieval infrastructure, and LLM-driven workflows are evolving across developer tooling, AI platforms, analytics teams, and modern search research.Andrey Vasnetsov (Qdrant) explained how Qdrant was born from the need to combine database-style querying with vector similarity search—something he first
How to Build and Evaluate AI systems in the Age of LLMs - Hugo Bowne-Anderson
In this talk, Hugo Bowne-Anderson, an independent data and AI consultant, educator, and host of the podcasts Vanishing Gradients and High Signal, shares his journey from academic research and curriculum design at DataCamp to advising teams at Netflix, Meta, and the US Air Force. Together, we explore how to build reliable, production-ready AI systems—from prompt evaluation and dataset design to emb
From Biotechnology to Bioinformatics Software - Sebastian Ayala Ruano
In this talk, Sebastian, a bioinformatics researcher and software engineer, shares his inspiring journey from wet lab biotechnology to computational bioinformatics. Hosted by Data Talks Club, this session explores how data science, AI, and open-source tools are transforming modern biological research — from DNA sequencing to metagenomics and protein structure prediction.You’ll learn about: - The d
Lessons from Applied AI: Tesla, Waymo, and Beyond - Aishwarya Jadhav
In this episode, we talked with Aishwarya Jadhav, a machine learning engineer whose career has spanned Morgan Stanley, Tesla, and now Waymo. Aishwarya shares her journey from big data in finance to applied AI in self-driving, gesture understanding, and computer vision. She discusses building an AI guide dog for the visually impaired, contributing to malaria mapping in Africa, and the challenges of
Building reliable AI products in the era of Gen AI and Agents - Ranjitha Kulkarni
In this episode, we talked with Ranjitha Kulkarni, a machine learning engineer with a rich career spanning Microsoft, Dropbox, and now NeuBird AI. Ranjitha shares her journey into ML and NLP, her work building recommendation systems, early AI agents, and cutting-edge LLM-powered products. She offers insights into designing reliable AI systems in the new era of generative AI and agents, and how con
From Theme Parks to Tesla: Building Data Products That Work
In this episode, we talked with Abouzar Abbaspour, a data engineer whose career spans software engineering in Iran, building crowd and recommendation systems at a Dutch theme park, deploying large-scale ML models at Bol.com, and now working at Tesla. Abouzar shares how he bridged diverse industries, tackled real-world data challenges, and adapted to new roles while keeping a hands-on approach to m
From Semiconductors to Machine Learning: A Career in Data and Teaching
In this episode, we chat with Dashel Ruiz, whose journey spans semiconductors, machine learning, and teaching. Dashel shares how he transitioned from hardware to data science, navigated complex projects in diverse industries, and now combines technical expertise with a passion for teaching. Tune in to hear insights on building a career in data, mastering new technologies, and making an impact both
Lessons from Two Decades of AI - Micheal Lanham
In this episode, we talk with Michael Lanham, an AI and software innovator with over two decades of experience spanning game development, fintech, oil and gas, and agricultural tech. Michael shares his journey from building neural network-based games and evolutionary algorithms to writing influential books on AI agents and deep learning. He offers insights into the evolving AI landscape, practical
Berlin PyData 2025 Conference Interviews
At PyData Berlin, community members and industry voices highlighted how AI and data tooling are evolving across knowledge graphs, MLOps, small-model fine-tuning, explainability, and developer advocacy.- Igor Kvachenok (Leuphana University / ProKube) combined knowledge graphs with LLMs for structured data extraction in the polymer industry, and noted how MLOps is shifting toward LLM-focused workflo
From Astronomy to Applied ML - Daniel Egbo
In this episode, we talk with Daniel, an astrophysicist turned machine learning engineer and AI ambassador. Daniel shares his journey bridging astronomy and data science, how he leveraged live courses and public knowledge sharing to grow his skills, and his experiences working on cutting-edge radio astronomy projects and AI deployments. He also discusses practical advice for beginners in data and
Berlin Buzzwords 2025 Conference Interviews
At Berlin Buzzwords, industry voices highlighted how search is evolving with AI and LLMs.- Kacper Łukawski (Qdrant) stressed hybrid search (semantic + keyword) as core for RAG systems and promoted efficient embedding models for smaller-scale use.- Manish Gill (ClickHouse) discussed auto-scaling OLAP databases on Kubernetes, combining infrastructure and database knowledge.- André Charton (Kleinanze
From Medicine to Machine Learning: How Public Learning Turned into a Career - Pastor Soto
In this episode, We talked with Pastor, a medical doctor who built a career in machine learning while studying medicine. Pastor shares how he balanced both fields, leveraged live courses and public sharing to grow his skills, and found opportunities through freelancing and mentoring.TIMECODES00:00 Pastor’s background and early programming journey06:05 Learning new tools and skills on the job while
How to Rebuild Data Trust? Mindful Data Strategy and Maintenance vs Innovation - Lior Barak
Struggling with data trust issues, dashboard drama, or constant pipeline firefighting? In this deep‑dive interview, Lior Barak shows you how to shift from a reactive “fix‑it” culture to a mindful, impact‑driven practice rooted in Zen/Wabi‑Sabi principles.You’ll learn:Why 97 % of CEOs say they use data, but only 24 % call themselves data‑drivenThe traffic‑light dashboard pattern (green / yellow / r
From Simulations to Freelance Data Engineering: Orell's Journey Out of Academia and Into Consulting - Orell Garten
In this episode, we talk with Orell about his journey from electrical engineering to freelancing in data engineering. Exploring lessons from startup life, working with messy industrial data, the realities of freelancing, and how to stay up to date with new tools. Topics covered: Why Orel left a PhD and a simulation‑focused start‑up after Covid hitWhat he learned trying (and failing) to commerciali
Can You Quit Your Job and Still Succeed as a Data Freelancer?
Thinking about swapping your 9‑to‑5 for client work, but worried that a long German–style notice period will kill your chances? In this live interview, seven‑year data‑freelance veteran Dimitri walks through his experience of taking his freelance career to the next level.About the Speaker: Dimitri Visnadi is an independent data consultant with a focus on data strategy. He has been consulting comp
From Hackathons to Developer Advocacy - Will Russel
In this podcast episode, we talked with Will Russell about From Hackathons to Developer Advocacy.About the Speaker: Will Russell is a Developer Advocate at Kestra, known for his videos on workflow orchestration. Previously, Will built open source education programs to help up and coming developers make their first contributions in open source. With a passion for developer education, Will creates t
Build a Strong Career in Data - Lavanya Gupta
In this podcast episode, we talked with Lavanya Gupta about Building a Strong Career in Data.About the Speaker: Lavanya is a Carnegie Mellon University (CMU) alumni of the Language Technologies Institute (LTI). She works as a Sr. AI/ML Applied Associate at JPMorgan Chase in their specialized Machine Learning Center of Excellence (MLCOE) vertical. Her latest research on long-context evaluation of L
From Supply Chain Management to Digital Warehousing and FinOps - Eddy Zulkifly
In this podcast episode, we talked with Eddy Zulkifly about From Supply Chain Management to Digital Warehousing and FinOpsAbout the Speaker: Eddy Zulkifly is a Staff Data Engineer at Kinaxis, building robust data platforms across Google Cloud, Azure, and AWS. With a decade of experience in data, he actively shares his expertise as a Mentor on ADPList and Teaching Assistant at Uplimit. Previously,
Data Intensive AI - Bartosz Mikulski
In this podcast episode, we talked with Bartosz Mikulski about Data Intensive AI.About the Speaker:Bartosz is an AI and data engineer. He specializes in moving AI projects from the good-enough-for-a-demo phase to production by building a testing infrastructure and fixing the issues detected by tests. On top of that, he teaches programmers and non-programmers how to use AI. He contributed one chapt
MLOps in Corporations and Startups - Nemanja Radojkovic
In this podcast episode, we talked with Nemanja Radojkovic about MLOps in Corporations and Startups.About the Speaker: Nemanja Radojkovic is Senior Machine Learning Engineer at Euroclear.In this event,we’re diving into the world of MLOps, comparing life in startups versus big corporations. Joining us again is Nemanja, a seasoned machine learning engineer with experience spanning Fortune 500 compan
Trends in Data Engineering – Adrian Brudaru
In this podcast episode, we talked with Adrian Brudaru about the past, present and future of data engineering.About the speaker:Adrian Brudaru studied economics in Romania but soon got bored with how creative the industry was, and chose to go instead for the more factual side. He ended up in Berlin at the age of 25 and started a role as a business analyst. At the age of 30, he had enough of start
Competitive Machine Leaning And Teaching – Alexander Guschin
In this podcast episode, we talked with Alexander Guschin about launching a career off Kaggle.About the Speaker: Alexander Guschin is a Machine Learning Engineer with 10+ years of experience, a Kaggle Grandmaster ranked 5th globally, and a teacher to 100K+ students. He leads DS and SE teams and contributes to open-source ML tools.0:00 Starting with Machine Learning: Challenges and Early Steps 13:0
Redefining AI Infrastructure: Open-Source, Chips, and the Future Beyond Kubernetes – Andrey Cheptsov
In this podcast episode, we talked with Andrey Cheptsov about The future of AI infrastructure.About the Speaker:Andrey Cheptsov is the founder and CEO of dstack, an open-source alternative to Kubernetes and Slurm, built to simplify the orchestration of AI infrastructure. Before dstack, Andrey worked at JetBrains for over a decade helping different teams make the best developer tools.During the ev
Linguistics and Fairness - Tamara Atanasoska
In this podcast episode, we talked with Tamara Atanasoska about building fair AI systems.About the Speaker:Tamara works on ML explainability, interpretability and fairness as Open Source Software Engineer at probable. She is a maintainer of fairlearn, contributor to scikit-learn and skops. Tamara has both computer science/ software engineering and a computational linguistics(NLP) background.Duri
Career choices, transitions and promotions in and out of tech - Agita Jaunzeme
In this podcast episode, we talked with Agita Jaunzeme about Career choices, transitions and promotions in and out of tech.
About the Speaker:
Agita has designed a career spanning DevOps/DataOps engineering, management, community building, education, and facilitation. She has worked on projects across corporate, startup, open source, and non-governmental sectors. Following her passion, she found
Career advice, learning, and featuring women in ML and AI - Isabella Bicalho
In this podcast episode, we talked with Isabella Bicalho about Career advice, learning, and featuring women in ML and AI.
About the Speaker:
Isabella is a Machine Learning Engineer and Data Scientist with three years of hands-on AI development experience. She draws upon her early computational research expertise to develop ML solutions. While contributing to open-source projects, she runs a news
AI in Industry: Trust, Return on Investment and Future - Maria Sukhareva
Reflection on an Almost Two-Year Journey of Generative AI in Industry – Maria Sukhareva
About the speaker:
Maria Sukhareva is a principal key expert in Artificial Intelligence in Siemens with over 15 years of experience at the forefront of generative AI technologies. Known for her keen eye for technological innovation, Maria excels at transforming cutting-edge AI research into practical, value-d
Large Hadron Collider and Mentorship – Anastasia Karavdina
We talked about:
00:00 DataTalks.Club intro
00:00 Large Hadron Collider and Mentorship
02:35 Career overview and transition from physics to data science
07:02 Working at the Large Hadron Collider
09:19 How particles collide and the role of detectors
11:03 Data analysis challenges in particle physics and data science similarities
13:32 Team structure at the Large Hadron Collider
20:05 Explaining th
MLOps as a Team - Raphaël Hoogvliets
We talked about:
00:00 DataTalks.Club intro
02:34 Career journey and transition into MLOps
08:41 Dutch agriculture and its challenges
10:36 The concept of "technical debt" in MLOps
13:37 Trade-offs in MLOps: moving fast vs. doing things right
14:05 Building teams and the role of coordination in MLOps
16:58 Key roles in an MLOps team: evangelists and tech translators
23:01 Role of the MLOps team in
Using Data to Create Liveable Cities - Rachel Lim
We talked about:
00:00 DataTalks.Club intro
01:56 Using data to create livable cities
02:52 Rachel's career journey: from geography to urban data science
04:20 What does a transport scientist do?
05:34 Short-term and long-term transportation planning
06:14 Data sources for transportation planning in Singapore
08:38 Rachel's motivation for combining geography and data science
10:19 Urban design and
DataTalks.Club 4th Anniversary AMA Podcast – Alexey Grigorev and Johanna Bayer
We talked about:
00:00 DataTalks.Club intro
00:00 DataTalks.Club anniversary "Ask Me Anything" event with Alexey Grigorev
02:29 The founding of DataTalks .Club
03:52 Alexey's transition from Java work to DataTalks.Club
04:58 Growth and success of DataTalks.Club courses
12:04 Motivation behind creating a free-to-learn community
24:03 Staying updated in data science through pet projects
26 :
Human-Centered AI for Disordered Speech Recognition - Katarzyna Foremniak
We talked about:
00:00 DataTalks.Club intro
08:06 Background and career journey of Katarzyna
09:06 Transition from linguistics to computational linguistics
11:38 Merging linguistics and computer science
15:25 Understanding phonetics and morpho-syntax
17:28 Exploring morpho-syntax and its relation to grammar
20:33 Connection between phonetics and speech disorders
24:41 Improvement of voice recognit
DataOps, Observability, and The Cure for Data Team Blues - Christopher Bergh
0:00
hi everyone Welcome to our event this event is brought to you by data dos club which is a community of people who love
0:06
data and we have weekly events and today one is one of such events and I guess we
0:12
are also a community of people who like to wake up early if you're from the states right Christopher or maybe not so
0:19
much because this is the time we usually have uh uh our ev
Working as a Core Developer in the Scikit-Learn Universe - Guillaume Lemaître
In this podcast episode, we talked with Guillaume Lemaître about navigating scikit-learn and imbalanced-learn.
🔗 CONNECT WITH Guillaume Lemaître
LinkedIn - https://www.linkedin.com/in/guillaume-lemaitre-b9404939/
Twitter - https://x.com/glemaitre58
Github - https://github.com/glemaitre
Website - https://glemaitre.github.io/
🔗 CONNECT WITH DataTalksClub
Join the community - https://datatalks-cl
Building a Domestic Risk Assessment Tool - Sabina Firtala
Links:
LinkedIn:https://www.linkedin.com/company/frontline100/
Ba Linh Le's LinkedIn: https://www.linkedin.com/in/ba-linh-le-/
Sabrina's LinkedIn: https://www.linkedin.com/in/sabina-firtala/
Twitter: https://x.com/frontline_100?mx=2
Website: https://www.frontline100.com/
Free LLM course: https://github.com/DataTalksClub/llm-zoomcamp
Join DataTalks.Club: https://datatalks.
Berlin Buzzwords 2024
We stream the podcasts on YouTube, where each session is also recorded and published on our channel, complete with timestamps, a transcript, and important links.
You can access all the podcast episodes here - https://datatalks.club/podcast.html
📚Check our free online courses
ML Engineering course - http://mlzoomcamp.com
Data Engineering course - https://github.com/DataTalksClub/data-engineering-
Community Building and Teaching in AI & Tech - Erum Afzal
We talked about:
Erum's Background
Omdena Academy and Erum’s Role There
Omdena’s Community and Projects
Course Development and Structure at Omdena Academy
Student and Instructor Engagement
Engagement and Motivation
The Role of Teaching in Community Building
The Importance of Communities for Career Building
Advice for Aspiring Instructors and Freelancers
DS and ML Talent Mark
Working in Open Source - Probabl.ai and sklearn - Vincent Warmerdam
We talked about:
Vincent’s Background
SciKit Learn’s History and Company Formation
Maintaining and Transitioning Open Source Projects
Teaching and Learning Through Open Source
Role of Developer Relations and Content Creation
Teaching Through Calm Code and The Importance of Content Creation
Current Projects and Future Plans for Calm Code
Data Processing Tricks and The Importance of I
AI for Ecology, Biodiversity, and Conservation - Tanya Berger-Wolf
Links:
Biodiversity and Artificial Intelligence pdf: https://www.gpai.ai/projects/responsible-ai/environment/biodiversity-and-AI-opportunities-recommendations-for-action.pdf
Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
Knowledge Graphs and LLMs Across Academia and Industry - Anahita Pakiman
We talked about:
Anahita's Background
Mechanical Engineering and Applied Mechanics
Finite Element Analysis vs. Machine Learning
Optimization and Semantic Reporting
Application of Knowledge Graphs in Research
Graphs vs Tabular Data
Computational graphs
Graph Data Science and Graph Machine Learning
Combining Knowledge Graphs and Large Language Models (LLMs)
Practical Applicati
Inclusive Data Leadership Coaching - Tereza Iofciu
We talked about:
Tereza’s background
Switching from an Individual Contributor to Lead
Python Pizza and the pizza management metaphor
Learning to figure things out on your own and how to receive feedback
Tereza as a leadership coach
Podcasts
Tereza’s coaching framework (selling yourself vs bragging)
The importance of retrospectives
The importance of communication and active listeni
Building Production Search Systems - Daniel Svonava
Links:
VectorHub: https://superlinked.com/vectorhub/?utm_source=community&utm_medium=podcast&utm_campaign=datatalks
Daniel's LinkedIn: https://www.linkedin.com/in/svonava/
Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
This podcast is s
Building Machine Learning Products - Reem Mahmoud
We talked about:
Reem’s background
Context-aware sensing and transfer learning
Shifting focus from PhD to industry
Reem’s experience with startups and dealing with prejudices towards PhDs
AI interviewing solution
How candidates react to getting interviewed by an AI avatar
End-to-end overview of a machine learning project
The pitfalls of using LLMs in your process
Mitigating biase
Make an Impact Through Volunteering Open Source Work - Sara EL-ATEIF
We talked about:
Sara’s background
On being a Google PhD fellow
Sara’s volunteer work
Finding AI volunteer work
Sara’s Fruit Punch challenge
How to take part in AI challenges
AI Wonder Girls
Hackathons
Things people often miss in AI projects and hackathons
Getting creative
Fostering your social media
Tips on applying for volunteer projects
Why it’s worth doing volunteer pr
Accelerating The Job Hunt for The Perfect Job in Tech - Sarah Mestiri
We talked about:
Sarah’s background
How Sarah became a coach and found her niche
Sarah’s clients
How Sarah helps her clients find the perfect job
Finding a specialization
Informational interviews
Building a connection for mutual benefit
The networking strategy
Listing your projects in the CV
The importance of doing research yourself and establishing your interests
How to land
Machine Learning Engineering in Finance - Nemanja Radojkovic
We talked about:
Nemanja’s background
When Nemanja first work as a data person
Typical problems that ML Ops folks solve in the financial sector
What Nemanja currently does as an ML Engineer
The obstacle of implementing new things in financial sector companies
Going through the hurdles of DevOps
Working with an on-premises cluster
“ML Ops on a Shoestring” (You don’t need fancy stuf
Stock Market Analysis with Python and Machine Learning - Ivan Brigida
We talked about:
Ivan’s background
How Ivan became interested in investing
Getting financial data to run simulations
Open, High, Low, Close, Volume
Risk management strategy
Testing your trading strategies
Sticking to your strategy
Important metrics and remembering about trading fees
Important features
Deployment
How DataTalks.Club courses helped Ivan
Ivan’s site and course s
Bayesian Modeling and Probabilistic Programming - Rob Zinkov
We talked about:
Rob’s background
Going from software engineering to Bayesian modeling
Frequentist vs Bayesian modeling approach
About integrals
Probabilistic programming and samplers
MCMC and Hakaru
Language vs library
Encoding dependencies and relationships into a model
Stan, HMC (Hamiltonian Monte Carlo) , and NUTS
Sources for learning about Bayesian modeling
Reaching out t
Navigating Challenges and Innovations in Search Technologies - Atita Arora
We talked about:
Atita’s background
How NLP relates to search
Atita’s experience with Lucidworks and OpenSource Connections
Atita’s experience with Qdrant and vector databases
Utilizing vector search
Major changes to search Atita has noticed throughout her career
RAG (Retrieval-Augmented Generation)
Building a chatbot out of transcripts with LLMs
Ingesting the data and evaluating
The Entrepreneurship Journey: From Freelancing to Starting a Company - Adrian Brudaru
We talked about:
Adrian’s background
The benefits of freelancing
Having an agency vs freelancing
What let Adrian switch over from freelancing
The conception of DLT (Growth Full Stack)
The investment required to start a company
Growth through the provision of services
Growth through teaching (product-market fit)
Moving on to creating docs
Adrian’s current role
Strategic partner
Become a Data Freelancer - Dimitri Visnadi
We talked about:
Dimitri’s background
The first steps of transitioning into freelance
Working with recruiters (contracting)
Deciding on what to charge for your services
Establishing your network
Self-marketing
Contracting vs freelancing
Which channel is better for those starting out?
Cutting out the middleman
Where to look for clients and how to vet them
The different way of g
AI for Digital Health - Maria Bruckert
We talked about:
Maria’s background
Deciding to go into telecare (healthcare)
Current difficulties in healthcare
Getting into the healthcare industry as a lifestyle brand
The importance of a plan B and being flexible
What is SQIN and the importance of communication
Going from lipstick to skin health analysis
The importance of community and broadening your audience
The importance
Cracking the Code: Machine Learning Made Understandable - Christoph Molnar
We talked about:
Christoph’s background
Kaggle and other competitions
How Christoph became interested in interpretable machine learning
Interpretability vs Accuracy
Christoph’s current competition engagement
How Christoph chooses topics for books
Why Christoph started the writing journey with a book
Self-publishing vs via a publisher
Christoph’s other books
What is conformal pre
The Unwritten Rules for Success in Machine Learning - Jack Blandin
We talked about:
Jack’s background
Transitioning from IC to management
Lesson not taught in traditional school
The importance of people’s perception, trust, and respect
How soft skills are relevant to machine learning
How to put on a salesman hat in machine learning management
The importance of visuals and building a POC as fast as possible
1st Rule of Machine Learning – don’t be af
From a Research Scientist at Amazon to a Machine learning/AI Consultant - Verena Webber
Links:
Mini sound bath: https://www.youtube.com/watch?v=g-lDrcSqcrQ
Free ML Engineering course: http://mlzoomcamp.com
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
From Marketing to Product Owner in Search - Lera Kaimashnіkova
We talked about:
Lera’s background
Lera’s move from Ukraine to Germany
The transition from Marketing to Product Ownership
The importance of communication and one-on-ones
The role of Product Owner
Utilizing Scrum as a Product Owner
Building teams and cross-functionality
Lera’s experience learning about search
The importance of having both technical knowledge and business context
Collaborative Data Science in Business - Ioannis Mesionis
Links:
LinkedIn: https://www.linkedin.com/in/ioannis-mesionis/
Github: https://github.com/ioannismesionis
Website: https://ioannismesionis.github.io/
Free ML Engineering course: http://mlzoomcamp.com
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
Bridging Data Science and Healthcare - Eleni Stamatelou
Free ML Engineering course: http://mlzoomcamp.com
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
DataTalks.Club Anniversary Interview - Alexey Grigorev, Johanna Bayer
Free ML Engineering course: http://mlzoomcamp.com
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html
Data Engineering for Fraud Prevention - Angela Ramirez
We talked about:
Angela's background
Angela's role at Sam's Club
The usefulness of knowing ML as a data engineer
Angela's career path
Transitioning from data analyst to data engineer/system designer
Best practices for system design and data engineering
Working with document databases
Working with network-based databases
Detecting fraud with a network-based database
From Data Manager to Data Architect - Loïc Magnien
We talked about:
Loïc's background
Data management
Loïc's transition to data engineer
Challenges in the transition to data engineering
What is a data architect?
The output of a data architect's work
Establishing metrics and dimensions
The importance of communication
Setting up best practices for the team
Staying relevant and tech-watching
Setting up specifications
Pragmatic and Standardized MLOps - Maria Vechtomova
We talked about:
Maria's background
Marvelous MLOps
Maria's definition of MLOps
Alternate team setups without a central MLOps team
Pragmatic vs non-pragmatic MLOps
Must-have ML tools (categories)
Maturity assessment
What to start with in MLOps
Standardized MLOps
Convincing DevOps to implement
Understanding what the tools are used for instead of knowing all the tools
Democratizing Causality - Aleksander Molak
We talked about:
Aleksander's background
Aleksander as a Causal Ambassador
Using causality to make decisions
Counterfactuals and and Judea Pearl
Meta-learners vs classical ML models
Average treatment effect
Reducing causal bias, the super efficient estimator, and model uplifting
Metrics for evaluating a causal model vs a traditional ML model
Is the added complexity of a causal
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