All with descriptions

Author: kavaivaleri

_podcast/no-timestamps/s10e03-mlops-architect.md

@@ -13,7 +13,7 @@ links:
   youtube: https://www.youtube.com/watch?v=p1gVaS4Zx5M
 season: 10
 short: MLOps Architect
-title: "MLOps Architect Guide: Production Model Monitoring, Data Observability & Tooling"
+title: 'MLOps Architect Guide: Production Model Monitoring, Data Observability & Tooling'
 transcript:
 - line: This week, we'll talk about being an MLOps architect. We have a special yesterday,
     Danny. Danny and I met more than one year ago – slightly more, I guess. I wasn't
@@ -1263,6 +1263,8 @@ transcript:
   sec: 3587
   time: '59:47'
   who: Danny
+description: Master MLOps, model monitoring & data observability with guidance on
+  production observability, ETL root causes, tooling trade-offs, ONNX, build vs buy.
 ---
 
 Links:

_podcast/no-timestamps/s10e04-lessons-learned-about-data-&-ai-at-enterprises.md

@@ -13,7 +13,8 @@ links:
   youtube: https://www.youtube.com/watch?v=Vms29u9xC3k
 season: 10
 short: Lessons Learned About Data & AI at Enterprises
-title: "Scale Enterprise AI: Data-First Strategies, MLOps Best Practices & Realistic Experiments"
+title: 'Scale Enterprise AI: Data-First Strategies, MLOps Best Practices & Realistic
+  Experiments'
 transcript:
 - line: This week, we'll talk about machine learning and data at enterprises. We have
     a special guest today, Alexander. Alexander is responsible for data and artificial
@@ -1017,6 +1018,8 @@ transcript:
   sec: 3807
   time: '1:03:27'
   who: Alexander
+description: Discover data-first Enterprise AI strategies and MLOps best practices—learn
+  realistic experiments, CI/CD, governance, and align ML to business impact.
 ---
 
 Links:

_podcast/no-timestamps/s10e05-growing-data-engineering-team-in-scale-up.md

@@ -13,7 +13,8 @@ links:
   youtube: https://www.youtube.com/watch?v=acJ6sVqKOUk
 season: 10
 short: Growing Data Engineering Team in a Scale-Up
-title: "Scale Data Engineering Teams: Build Self‑Service Data Platforms, Hire Senior Engineers & Use Kafka"
+title: 'Scale Data Engineering Teams: Build Self‑Service Data Platforms, Hire Senior
+  Engineers & Use Kafka'
 transcript:
 - line: This week, we will talk about growing a data engineering team in a scale-up.
     We have a special guest today, Mehdi. I know Mehdi as a content creator and a
@@ -1074,6 +1075,8 @@ transcript:
   sec: 3802
   time: '1:03:22'
   who: Mehdi
+description: 'Master scaling data engineering teams: build self-service data platforms,
+  hire senior engineers, deploy Kafka best practices to boost velocity, onboarding.'
 ---
 
 Links:

_podcast/no-timestamps/s10e06-data-mesh-101.md

@@ -13,7 +13,8 @@ links:
   youtube: https://www.youtube.com/watch?v=346N_pCtYZU
 season: 10
 short: Data Mesh 101
-title: "Data Mesh Implementation: Build Decentralized Data Products, Contracts & Federated Governance"
+title: 'Data Mesh Implementation: Build Decentralized Data Products, Contracts & Federated
+  Governance'
 transcript:
 - line: This week we will talk about Data Mesh. We have a special guest today, Zhamak.
     Zhamak is a principal Technology Consultant at ThoughtWorks and she's the inventor
@@ -994,6 +995,8 @@ transcript:
   sec: 3739
   time: '1:02:19'
   who: Zhamak
+description: Discover Data Mesh strategies, data contracts and federated governance
+  to build decentralized data products, improve data quality, and scale adoption.
 ---
 
 Links:

_podcast/no-timestamps/s10e07-dataset-creation-and-curation.md

@@ -13,7 +13,8 @@ links:
   youtube: https://www.youtube.com/watch?v=QggWydGrWoo
 season: 10
 short: Dataset Creation and Curation
-title: "Practical Guide to Dataset Creation & Annotation for NLP: Active Learning, Weak Supervision, Tools"
+title: 'Practical Guide to Dataset Creation & Annotation for NLP: Active Learning,
+  Weak Supervision, Tools'
 transcript:
 - line: This week, we'll talk about dataset creation and annotation – creation, curation,
     and annotation. We have a special guest today, Chris. Chris has six years of experience
@@ -1042,6 +1043,8 @@ transcript:
   sec: 3902
   time: '1:05:02'
   who: Alexey
+description: 'Discover dataset creation, annotation & active learning: practical annotation
+  UX, quality metrics, prototyping tips and tooling to accelerate NLP models.'
 ---
 
 Links:

_podcast/no-timestamps/s10e08-leading-data-research.md

@@ -13,7 +13,7 @@ links:
   youtube: https://www.youtube.com/watch?v=vZLlpsUlchQ
 season: 10
 short: Leading Data Research
-title: "Build Data Science Programs, Democratize HPC & Scale Graph Analytics with Arkouda"
+title: Build Data Science Programs, Democratize HPC & Scale Graph Analytics with Arkouda
 transcript:
 - line: This week, we'll talk about being a professor and leading data research. We
     have a special guest today, David. David is the director of the Institute for
@@ -1129,6 +1129,9 @@ transcript:
   sec: 3890
   time: '1:04:50'
   who: Alexey
+description: Learn to build data science programs, democratize HPC and scale graph
+  analytics with Arkouda - practical curriculum, performance tips and recruitment
+  tips
 ---
 
 Links:

_podcast/no-timestamps/s10e09-responsible-and-explainable-ai.md

@@ -13,7 +13,8 @@ links:
   youtube: https://www.youtube.com/watch?v=8Eb5mG-pC3o
 season: 10
 short: Responsible and Explainable AI
-title: "Responsible & Explainable AI: Practical Guide to Bias Detection, Fairness & Governance"
+title: 'Responsible & Explainable AI: Practical Guide to Bias Detection, Fairness
+  & Governance'
 transcript:
 - line: This week, we'll talk about responsible and Explainable AI. We have a special
     guest today, Supreet. Supreet is an assistant VP in data strategy at Morgan Stanley.
@@ -1158,6 +1159,9 @@ transcript:
   sec: 3630
   time: '1:00:30'
   who: Alexey
+description: Discover Responsible AI & Explainable AI tactics for bias detection,
+  fairness checks and governance, practical tools to build trustworthy, compliant
+  ML models.
 ---
 
 Links:

_podcast/no-timestamps/s11e01-from-testing-phones-to-managing-nlp-projects.md

@@ -13,7 +13,8 @@ links:
   youtube: https://www.youtube.com/watch?v=-xumbiXOlA8
 season: 11
 short: From Testing Phones to Managing NLP Projects
-title: "Transition from QA to Machine Learning & Data Engineering: Projects, Cloud & Interview Prep"
+title: 'Transition from QA to Machine Learning & Data Engineering: Projects, Cloud
+  & Interview Prep'
 transcript:
 - line: This week, we'll talk about career transitioning from quality assurance to
     machine learning. We have a special guest today, Alvaro. Alvaro worked in the
@@ -1257,6 +1258,8 @@ transcript:
   sec: 3759
   time: '1:02:39'
   who: Alexey
+description: 'Master the transition to machine learning & data engineering: build
+  cloud-deployed projects, sharpen interview prep, and revamp your CV to land offers.'
 ---
 
 Links:

_podcast/no-timestamps/s11e02-data-science-career-development.md

@@ -13,7 +13,7 @@ links:
   youtube: https://www.youtube.com/watch?v=i1NHRroQClQ
 season: 11
 short: Data Science Career Development
-title: "Data Science Career Guide: Hiring, Managing & Growing Teams in B2B SaaS"
+title: 'Data Science Career Guide: Hiring, Managing & Growing Teams in B2B SaaS'
 transcript:
 - line: This week we'll talk about data science career development. We have a special
     guest today, Katie. Am I pronouncing it correctly? Katie?
@@ -1190,6 +1190,9 @@ transcript:
   sec: 3613
   time: '1:00:13'
   who: Alexey
+description: Learn hiring & management tactics for data science in B2B SaaS — hiring,
+  onboarding, mentorship, and career growth strategies to build scalable analytics
+  teams.
 ---
 
 Links:

_podcast/no-timestamps/s11e03-from-data-science-to-dataops.md

@@ -13,7 +13,8 @@ links:
   youtube: https://www.youtube.com/watch?v=lem7knxqNzg
 season: 11
 short: From Data Science to DataOps
-title: "DataOps & GitOps for Data Teams: Onboarding, IaC, Reproducibility & Production Best Practices"
+title: 'DataOps & GitOps for Data Teams: Onboarding, IaC, Reproducibility & Production
+  Best Practices'
 transcript:
 - line: This week, we'll talk about DataOps. We have a special guest today, Tomasz.
     Tomasz is a DataOps who lives in Poland, in Poznan. After working in product analytics,
@@ -964,6 +965,8 @@ transcript:
   sec: 4009
   time: '1:06:49'
   who: Alexey
+description: Master DataOps, GitOps and IaC best practices for reproducibility, onboarding
+  and production reliability — actionable Git workflows, Terraform, Docker tips.
 ---
 
 Links: