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 in the lab and the classroom.

TIMECODES

00:00 Dashel's unique career path from music to semiconductors

06:16 The transition into data and software engineering at Microchip

11:44 Discovering machine learning to solve real problems in semiconductor manufacturing

20:40 How Dashel found and his experience with the Machine Learning Zoomcamp

29:33 The practical advantages of DataTalks.Club courses over other platforms

39:52 Overcoming challenges and the value of the learning community

48:10 Hands-on project experience: From image classification to Kaggle competitions

54:12 Staying motivated throughout the long-term course

59:55 The importance of deployment and full-stack ML skills

1:07:36 Closing thoughts on teaching and future courses

Connect with Dashel

• Linkedin - https://www.linkedin.com/in/dashel-ruiz-perez-2b036172/

Connect with DataTalks.Club:

• Join the community - https://datatalks.club/slack.html
• Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ
• Check other upcoming events - https://lu.ma/dtc-events
• GitHub: https://github.com/DataTalksClub
• LinkedIn - https://www.linkedin.com/company/datatalks-club/
• Twitter - https://twitter.com/DataTalksClub
• Website - https://datatalks.club/

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 uses of AI agents, and the future of generative AI in gaming and beyond.

TIMECODES

00:00 Micheal Lanham’s career journey and AI agent books

05:45 Publishing journey: AR, Pokémon Go, sound design, and reinforcement learning

10:00 Evolution of AI: evolutionary algorithms, deep learning, and agents

13:33 Evolutionary algorithms in prompt engineering and LLMs

18:13 AI agent books second edition and practical applications

20:57 AI agent workflows: minimalism, task breakdown, and collaboration

26:25 Collaboration and orchestration among AI agents

31:24 Tools and reasoning servers for agent communication

35:17 AI agents in game development and generative AI impact

38:57 Future of generative AI in gaming and immersive content

41:42 Coding agents, new LLMs, and local deployment

45:40 AI model trends and data scientist career advice

53:36 Cognitive testing, evaluation, and monitoring in AI

58:50 Publishing details and closing remarks

Connect with Micheal

• Linkedin - https://www.linkedin.com/in/micheal-lanham-189693123/

Connect with DataTalks.Club:

• Join the community - https://datatalks.club/slack.html

• Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...
• Check other upcoming events - https://lu.ma/dtc-events
• GitHub: https://github.com/DataTalksClub
• LinkedIn -   / datatalks-club  
• Twitter -   / datatalksclub  
• Website - https://datatalks.club/

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 workflows.

- Selim Nowicki (Distill Labs) introduced a platform that uses knowledge distillation to fine-tune smaller models efficiently, making model specialization faster and more accessible.

- Gülsah Durmaz (Architect & Developer) shared her transition from architecture to coding, creating Python tools for design automation and volunteering with PyData through PyLadies.

- Yashasvi Misra (Pure Storage) spoke on explainable AI, stressing accountability and compliance, and shared her perspective as both a data engineer and active Python community organizer.

- Mehdi Ouazza (MotherDuck) reflected on developer advocacy through video, workshops, and branding, showing how creative communication boosts adoption of open-source tools like DuckDB.

Igor Kvachenok

Master’s student in Data Science at Leuphana University of Lüneburg, writing a thesis on LLM-enhanced data extraction for the polymer industry. Builds RDF knowledge graphs from semi-structured documents and works at ProKube on MLOps platforms powered by Kubeflow and Kubernetes.

Connect: https://www.linkedin.com/in/igor-kvachenok/

Selim Nowicki

Founder of Distill Labs, a startup making small-model fine-tuning simple and fast with knowledge distillation. Previously led data teams at Berlin startups like Delivery Hero, Trade Republic, and Tier Mobility. Sees parallels between today’s ML tooling and dbt’s impact on analytics.

Connect: https://www.linkedin.com/in/selim-nowicki/

Gülsah Durmaz

Architect turned developer, creating Python-based tools for architectural design automation with Rhino and Grasshopper. Active in PyLadies and a volunteer at PyData Berlin, she values the community for networking and learning, and aims to bring ML into architecture workflows.

Connect: https://www.linkedin.com/in/gulsah-durmaz/

Yashasvi (Yashi) Misra

Data Engineer at Pure Storage, community organizer with PyLadies India, PyCon India, and Women Techmakers. Advocates for inclusive spaces in tech and speaks on explainable AI, bridging her day-to-day in data engineering with her passion for ethical ML.

Connect: https://www.linkedin.com/in/misrayashasvi/

Mehdi Ouazza

Developer Advocate at MotherDuck, formerly a data engineer, now focused on building community and education around DuckDB. Runs popular YouTube channels ("mehdio DataTV" and "MotherDuck") and delivered a hands-on workshop at PyData Berlin. Blends technical clarity with creative storytelling.

Connect: https://www.linkedin.com/in/mehd-io/

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 astronomy, and insights on career growth through community and continuous learning.TIMECODES00:00 Lunar eclipse story and Daniel’s astronomy career04:12 Electromagnetic spectrum and MEERKAT data explained10:39 Data analysis and positional cross-correlation challenges15:25 Physics behind radio star detection and observation limits16:35 Radio astronomy’s advantage and machine learning potential20:37 Radio astronomy progress and Daniel’s ML journey26:00 Python tools and experience with ZoomCamps31:26 Intel internship and exploring LLMs41:04 Sharing progress and course projects with orchestration tools44:49 Setting up Airflow 3.0 and building data pipelines47:39 AI startups, training resources, and NVIDIA courses50:20 Student access to education, NVIDIA experience, and beginner astronomy programs57:59 Skills, projects, and career advice for beginners59:19 Starting with data science or engineering1:00:07 Course sponsorship, data tools, and learning resourcesConnect with Daniel

• Linkedin -   / egbodaniel  

Connect with DataTalks.Club:

• Join the community - https://datatalks.club/slack.html
• Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...
• Check other upcoming events - https://lu.ma/dtc-events
• GitHub: https://github.com/DataTalksClub
• LinkedIn -   / datatalks-club  
• Twitter -   / datatalksclub  

• Website - https://datatalks.club/

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 (Kleinanzeigen) reflected on scaling search for millions of classifieds, moving from Solr/Elasticsearch toward vector search, while returning to a hands-on technical role.

- Filip Makraduli (Superlinked) introduced a vector-first framework that fuses multiple encoders into one representation for nuanced e-commerce and recommendation search.

- Brian Goldin (Voyager Search) emphasized spatial context in retrieval, combining geospatial data with AI enrichment to add the “where” to search.

- Atita Arora (Voyager Search) highlighted geospatial AI models, the renewed importance of retrieval in RAG, and the cautious but promising rise of AI agents.

Together, their perspectives show a common thread: search is regaining center stage in AI—scaling, hybridization, multimodality, and domain-specific enrichment are shaping the next generation of retrieval systems.

Kacper Łukawski

Senior Developer Advocate at Qdrant, he educates users on vector and hybrid search. He highlighted Qdrant’s support for dense and sparse vectors, the role of search with LLMs, and his interest in cost-effective models like static embeddings for smaller companies and edge apps.

Connect: https://www.linkedin.com/in/kacperlukawski/

Manish Gill

Engineering Manager at ClickHouse, he spoke about running ClickHouse on Kubernetes, tackling auto-scaling and stateful sets. His team focuses on making ClickHouse scale automatically in the cloud. He credited its speed to careful engineering and reflected on the shift from IC to manager.

Connect: https://www.linkedin.com/in/manishgill/

André Charton

Head of Search at Kleinanzeigen, he discussed shaping the company’s search tech—moving from Solr to Elasticsearch and now vector search with Vespa. Kleinanzeigen handles 60M items, 1M new listings daily, and 50k requests/sec. André explained his career shift back to hands-on engineering.

Connect: https://www.linkedin.com/in/andrecharton/

Filip Makraduli

Founding ML DevRel engineer at Superlinked, an open-source framework for AI search and recommendations. Its vector-first approach fuses multiple encoders (text, images, structured fields) into composite vectors for single-shot retrieval. His Berlin Buzzwords demo showed e-commerce search with natural-language queries and filters.

Connect: https://www.linkedin.com/in/filipmakraduli/

Brian Goldin

Founder and CEO of Voyager Search, which began with geospatial search and expanded into documents and metadata enrichment. Voyager indexes spatial data and enriches pipelines with NLP, OCR, and AI models to detect entities like oil spills or windmills. He stressed adding spatial context (“the where”) as critical for search and highlighted Voyager’s 12 years of enterprise experience.

Connect: https://www.linkedin.com/in/brian-goldin-04170a1/

Atita Arora

Director of AI at Voyager Search, with nearly 20 years in retrieval systems, now focused on geospatial AI for Earth observation data. At Berlin Buzzwords she hosted sessions, attended talks on Lucene, GPUs, and Solr, and emphasized retrieval quality in RAG systems. She is cautiously optimistic about AI agents and values the event as both learning hub and professional reunion.

Connect: https://www.linkedin.com/in/atitaarora/

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.

TIMECODES

00:00 Pastor’s background and early programming journey

06:05 Learning new tools and skills on the job while studying medicine

11:44 Balancing medical studies with data science work and motivation

13:48 Applying medical knowledge to data science and vice versa

18:44 Starting freelance work on Upwork and overcoming language challenges

24:03 Joining the machine learning engineering course and benefits of live cohorts

27:41 Engaging with the course community and sharing progress publicly

35:16 Using LinkedIn and social media for career growth and interview opportunities

41:03 Building reputation, structuring learning, and leveraging course projects

50:53 Volunteering and mentoring with DeepLearning.AI and Stanford Coding Place

57:00 Managing time and staying productive while studying medicine and machine learning

Connect with Pastor

• Twitter - https://x.com/PastorSotoB1
• Linkedin -   / pastorsoto  
• Github - https://github.com/sotoblanco
• Website - https://substack.com/@pastorsoto

Connect with DataTalks.Club:

• Join the community - https://datatalks.club/slack.html
• Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...
• Check other upcoming events - https://lu.ma/dtc-events
• GitHub: https://github.com/DataTalksClub
• LinkedIn -   / datatalks-club  
• Twitter -   / datatalksclub  
• Website - https://datatalks.club/

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‑driven

The traffic‑light dashboard pattern (green / yellow / red) that instantly tells execs whether numbers are safe to use

A practical rule for balancing maintenance, rollout, and innovation—and avoiding team burnout

How to quantify ROI on data products, kill failing legacy systems, and handle ad‑hoc exec requests without derailing roadmaps

Turning “imperfect” data into business value with mindful communication, root‑cause logs, and automated incident review loops

🕒 TIMECODES

00:00 Community and mindful data strategy

04:06 Career journey and product management insights

08:03 Wabi-sabi data and the trust crisis

11:47 AI, data imperfection, and trust challenges

20:05 Trust crisis examples and root cause analysis

25:06 Regaining trust through mindful data management

30:47 Traffic light system and effective communication

37:41 Communication gaps and team workload balance

39:58 Maintenance stress and embracing Zen mindset

49:29 Accepting imperfection and measuring impact

56:19 Legacy systems and managing executive requests

01:00:23 Role guidance and closing reflections

🔗 Connect with Lior

LinkedIn - https://www.linkedin.com/in/liorbarak

Website - https://cookingdata.substack.com/

Cooking Data newsletter: https://cookingdata.substack.com/

Product product lifecycle manager: https://app--data-product-lifecycle-manager-c81b10bb.base44.app/

🔗 Connect with DataTalks.Club

Join the community - https://datatalks.club/slack.html

Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/u/0/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ

Check other upcoming events - https://lu.ma/dtc-events

GitHub: https://github.com/DataTalksClub

LinkedIn - https://www.linkedin.com/company/datatalks-club/

Twitter - https://x.com/DataTalksClub

Website - https://datatalks.club/

🔗 Connect with Alexey

Twitter - https://x.com/Al_Grigor

Linkedin - https://www.linkedin.com/in/agrigorev/

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 hit
• What he learned trying (and failing) to commercialise medical‑imaging simulations
• The first freelance project and the long, quiet months that followed
• How he now finds clients, keeps projects small and delivers value quickly
• Typical work he does for industrial companies: parsing messy machine logs, building simple pipelines, adding structure later
• Favorite everyday tools (Python, DuckDB, a bit of C++) and the habit of blocking time for learning
• Advice for anyone thinking about freelancing: cash runway, networking, and focusing on problems rather than “perfect” tech choices

A practical conversation for listeners who are curious about moving from research or permanent roles into freelance data engineering.

🕒 TIMECODES

0:00 Orel’s career and move to freelancing

9:04 Startup experience and data engineering lessons

16:05 Academia vs. startups and starting freelancing

25:33 Early freelancing challenges and networking

34:22 Freelance data engineering and messy industrial data

43:27 Staying practical, learning tools, and growth

50:33 Freelancing challenges and client acquisition

58:37 Tools, problem-solving, and manual work

🔗 CONNECT WITH ORELL

Twitter - https://bsky.app/profile/orgarten.bsk...

LinkedIn - / ogarten

Github - https://github.com/orgarten

Website - https://orellgarten.com

🔗 CONNECT WITH DataTalksClub

Join the community - https://datatalks.club/slack.html

Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...

Check other upcoming events - https://lu.ma/dtc-events

GitHub: https://github.com/DataTalksClub

LinkedIn - / datatalks-club

Twitter - / datatalksclub

Website - https://datatalks.club/

🔗 CONNECT WITH ALEXEY

Connect with Alexey

Twitter - / al_grigor

Linkedin - / agrigorev

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 companies leading the marketing data space such as Unilever, Ferrero, Heineken, and Red Bull.

He has lived and worked in 6 countries across Europe in both corporate and startup organizations. He was part of data departments at Hewlett-Packard (HP) and a Google partnered consulting firm where he was working on data products and strategy.

Having received a Masters in Business Analytics with Computer Science from University College London and a Bachelor in Business Administration from John Cabot University, Dimitri still has close ties to academia and holds a mentor position in entrepreneurship at both institutions.

🕒 TIMECODES00:00 Dimitri’s journey from corporate to freelance data specialist05:41 Job tenure trends, tech career shifts, and freelance types10:50 Freelancing challenges, success, and finding clients17:33 Freelance market trends and Dimitri’s job board23:51 Starting points, top freelance skills, and market insights32:48 Building a lifestyle business: scaling and work-life balance45:30 Data Freelancer course and marketing for freelancers48:33 Subscription services and managing client relationships56:47 Pricing models and transitioning advice1:01:02 Notice periods, networking, and risks in freelancing transition

🔗 CONNECT WITH DataTalksClub

Join the community - https://datatalks.club/slack.html

Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...

Check other upcoming events - https://lu.ma/dtc-events

LinkedIn - / datatalks-club

Twitter - / datatalksclub

Website - https://datatalks.club/

🔗 CONNECT WITH DIMITRI

Linkedin - https://www.linkedin.com/in/visnadi/

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 technical video content and documentation that makes technologies more approachable for developers.

In this episode, we sit down with Will—developer advocate, content creator, and passionate community builder. We’ll hear about his unique path through tech, the lessons he’s learned, and his approach to making complex topics accessible and engaging. Whether you’re curious about open source, hackathons, or what it’s like to bridge the gap between developers and the broader tech community, this conversation is full of insights and inspiration.

🕒 TIMECODES

0:00 Introduction, career journeys, and video setup and workflow

10:41 From hackathons to open source: Early experiences and learning

16:04 Becoming a hackathon organizer and the value of soft skills

23:18 How to organize a hackathon, memorable projects, and creativity

33:39 Major League Hacking: Building community and scaling student programs

41:16 Mentorship, development environments, and onboarding in open source

49:14 Developer advocacy, content strategy, and video tips

57:16 Will’s current projects and future plans for content creation

🔗 CONNECT WITH DataTalksClub

Join the community - https://datatalks.club/slack.html

Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ

Check other upcoming events - https://lu.ma/dtc-events

LinkedIn - https://www.linkedin.com/company/datatalks-club/

Twitter - https://twitter.com/DataTalksClub

Website - https://datatalks.club/

🔗 CONNECT WITH WILL

LinkedIn - https://www.linkedin.com/in/wrussell1999/

Twitter - https://x.com/wrussell1999

GitHub - https://github.com/wrussell1999

Website - https://wrussell.co.uk/