Update course articles: curriculum, images, docs links, dates

alexeygrigorev · alexeygrigorev · commit af19e52a8e13 · 2026-05-11T16:57:49.000+02:00
- LLM Zoomcamp: update curriculum to match repo (minsearch, PGVector, agents),
  fix broken images, remove Elasticsearch/LangChain/Qdrant/Ollama/Hugging Face,
  update structured data and FAQ, add docs links, remove bold
- DE Zoomcamp: add Apache Flink, fix broken image, add docs links, update date
- ML Zoomcamp: add docs links, update date
- MLOps Zoomcamp: add docs links, update date
- AI Dev Tools Zoomcamp: add docs links, update date
- Guide article: fix LLM Zoomcamp tech stack, remove bold from overview,
  simplify cost text, make header title clickable, update date
diff --git a/_data/faqs/llm-zoomcamp.yml b/_data/faqs/llm-zoomcamp.yml
@@ -2,7 +2,7 @@
   answer: |
     The LLM Zoomcamp is a free, community-driven program by [DataTalks.Club](/) that teaches practical applications with large language models through hands-on project work.
     
-    This 10-week course covers a comprehensive [curriculum](#course-curriculum) with all materials open and available anytime on [GitHub](https://github.com/DataTalksClub/llm-zoomcamp). You'll work with an industry-standard stack including OpenAI API, Hugging Face, Elasticsearch, Ollama, Streamlit, Grafana, LangChain, and vector databases, and earn a [certificate](#can-i-get-a-certificate).
+    This 10-week course covers a comprehensive [curriculum](#course-curriculum) with all materials open and available anytime on [GitHub](https://github.com/DataTalksClub/llm-zoomcamp). You'll work with an industry-standard stack including OpenAI API, minsearch, PGVector, and Grafana, and earn a [certificate](#can-i-get-a-certificate).
 
 - question: "What does zoomcamp mean?"
   answer: |
@@ -96,7 +96,7 @@
 
 - question: "What tools and technologies will I learn?"
   answer: |
-    The course covers essential LLM tools and platforms including OpenAI API for LLM integration, Hugging Face for open-source models, Elasticsearch for vector search and text search, Ollama for running LLMs locally, Streamlit for building UIs, Grafana for monitoring, LangChain for LLM orchestration, and vector databases for efficient retrieval. You'll also learn evaluation techniques, monitoring best practices, and data ingestion pipelines.
+    The course covers essential LLM tools and platforms including OpenAI API for LLM integration, PGVector for vector search, Grafana for monitoring, and evaluation techniques. You'll also learn monitoring best practices, agent patterns, and data ingestion pipelines.
 
 - question: "What is the DataTalks.Club LLM community?"
   answer: |
diff --git a/_includes/course-structured-data/llm-zoomcamp-structured-data.html b/_includes/course-structured-data/llm-zoomcamp-structured-data.html
@@ -23,37 +23,37 @@
   "skills": [
     "Python",
     "OpenAI API",
-    "Elasticsearch",
-    "Qdrant",
-    "dlt",
+    "minsearch",
+    "sqlitesearch",
+    "PGVector",
     "Vector Search",
     "Embeddings",
     "RAG",
+    "OpenAI Responses API",
+    "ToyAIKit",
     "LLM-as-a-Judge",
     "Evaluation Frameworks",
     "Grafana",
     "Monitoring",
-    "LangChain",
     "Hybrid Search",
     "Reranking",
-    "OpenAI Function Calling",
     "LLM Engineering",
     "Retrieval Systems"
   ],
   "syllabusSections": [
     {
       "name": "Introduction to LLMs and RAG",
-      "description": "Build your first RAG pipeline with LLM fundamentals and text search using OpenAI API and Elasticsearch.",
+      "description": "Build your first RAG pipeline with LLM fundamentals and text search using OpenAI API, minsearch, and sqlitesearch.",
       "timeRequired": "P1W"
     },
     {
       "name": "Vector Search",
-      "description": "Create embeddings, index documents, and retrieve with semantic search using Qdrant and dlt.",
+      "description": "Generate embeddings, index documents, and retrieve with semantic search using sentence-transformers and PGVector.",
       "timeRequired": "P1W"
     },
     {
-      "name": "Agents (Bonus)",
-      "description": "Add agentic behavior and function calling to RAG pipelines using OpenAI Function Calling.",
+      "name": "Agents",
+      "description": "Add autonomous tool use and function calling to RAG pipelines using OpenAI Responses API and ToyAIKit.",
       "timeRequired": "P1W"
     },
     {
@@ -68,7 +68,7 @@
     },
     {
       "name": "Best Practices",
-      "description": "Optimize retrieval with hybrid search, reranking, and orchestration patterns using LangChain and hybrid search tools.",
+      "description": "Optimize retrieval with hybrid search and reranking.",
       "timeRequired": "P1W"
     },
     {
diff --git a/_posts/2023-08-17-machine-learning-zoomcamp.md b/_posts/2023-08-17-machine-learning-zoomcamp.md
@@ -17,7 +17,7 @@ related_posts:
 - mlops-zoomcamp.html
 - llm-zoomcamp.html
 - ai-dev-tools-zoomcamp-2025-free-course-to-master-coding-assistants-agents-and-automation.html
-date: 2025-11-25
+date: 2026-05-11
 charts: true
 datepublished: '2023-08-17'
 ---
@@ -457,6 +457,8 @@ The entire journey takes 4 months from start to certificate, and you'll be part
 
 ## Frequently Asked Questions
 
+For more details about how our courses work, check the [Zoomcamp logistics guide](https://datatalks.club/docs/courses/zoomcamp-logistics/){:target="_blank"}. You can also find more information about this course in the [ML Zoomcamp documentation](https://datatalks.club/docs/courses/ml-zoomcamp/){:target="_blank"}.
+
 {% include faq-accordion.html faqs=site.data.faqs.machine-learning-zoomcamp %}
 
 <div style="text-align: center; margin: 2em 0;">
diff --git a/_posts/2023-11-18-data-engineering-zoomcamp.md b/_posts/2023-11-18-data-engineering-zoomcamp.md
@@ -17,7 +17,7 @@ related_posts:
 - ai-dev-tools-zoomcamp-2025-free-course-to-master-coding-assistants-agents-and-automation.html
 layout: post
 datepublished: '2023-11-18'
-date: 2026-04-21
+date: 2026-05-11
 ---
 
 Breaking into data engineering takes real, hands-on experience with production tools, but most courses stop at theory.
@@ -476,6 +476,8 @@ We've collected some testimonials from our students who have completed the Data
 
 ## Frequently Asked Questions
 
+For more details about how our courses work, check the [Zoomcamp logistics guide](https://datatalks.club/docs/courses/zoomcamp-logistics/){:target="_blank"}. You can also find more information about this course in the [Data Engineering Zoomcamp documentation](https://datatalks.club/docs/courses/data-engineering-zoomcamp/){:target="_blank"}.
+
 {% include faq-accordion.html faqs=site.data.faqs.data-engineering-zoomcamp %}
 
 <div style="text-align: center; margin: 2em 0;">
diff --git a/_posts/2024-03-07-mlops-zoomcamp.md b/_posts/2024-03-07-mlops-zoomcamp.md
@@ -12,7 +12,7 @@ tags:
 - courses
 - mlops
 title: 'MLOps Zoomcamp: Free MLOps Course and Certification'
-date: 2025-11-25
+date: 2026-05-11
 related_posts:
 - guide-to-free-online-courses-at-datatalks-club.html
 - machine-learning-zoomcamp.html
@@ -261,6 +261,8 @@ Even if you join after the official start date, you can still follow along — b
 
 ## Frequently Asked Questions
 
+For more details about how our courses work, check the [Zoomcamp logistics guide](https://datatalks.club/docs/courses/zoomcamp-logistics/){:target="_blank"}.
+
 {% include faq-accordion.html faqs=site.data.faqs.mlops-zoomcamp %}
 
 <div style="text-align: center; margin: 2em 0;">
diff --git a/_posts/2024-04-11-guide-to-free-online-courses-at-datatalks-club.md b/_posts/2024-04-11-guide-to-free-online-courses-at-datatalks-club.md
@@ -12,7 +12,7 @@ authors:
 - valeriiakuka
 tags:
 - courses
-date: 2025-11-25
+date: 2026-05-11
 datepublished: '2024-04-11'
 ---
 
@@ -85,7 +85,7 @@ Here's a table that summarizes the key information about each course. Use it to
 <td style="padding: 12px; border: 1px solid #dee2e6;">Intermediate</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">Python, command line, Docker (no ML required)</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">LLMs, RAG, vector search, evaluation, production deployment</td>
-<td style="padding: 12px; border: 1px solid #dee2e6;">OpenAI API, LangChain, Hugging Face, Ollama, Qdrant, Elasticsearch</td>
+<td style="padding: 12px; border: 1px solid #dee2e6;">OpenAI API, minsearch, PGVector, Grafana, LangChain</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">AI chatbot that answers questions from your knowledge base</td>
 </tr>
 <tr>
@@ -351,7 +351,7 @@ You'll learn to use MLflow for experiment tracking, build automated training pip
 
 <figure>
 <img src="/images/posts/2024-04-11-guide-to-free-online-courses-at-datatalks-club/llm-zoomcamp-cover.png" alt="LLM Zoomcamp course cover" title="LLM Zoomcamp Course Cover - 10-Week Large Language Models and RAG Application Development" loading="lazy" style="max-width: 100%; height: auto; border: 1px solid #ddd; border-radius: 4px;" />
-<figcaption><p>LLM Zoomcamp 10-week program on building AI applications with large language models, covering RAG (retrieval-augmented generation), vector databases, evaluation techniques, and production deployment using OpenAI, LangChain, Hugging Face, and Ollama</p></figcaption>
+<figcaption><p>LLM Zoomcamp 10-week program on building AI applications with large language models, covering RAG (retrieval-augmented generation), vector search, evaluation techniques, and production deployment using OpenAI, PGVector, and Grafana</p></figcaption>
 </figure>
 
 <table style="width: 100%; border-collapse: collapse; margin-bottom: 1.5em;">
@@ -382,7 +382,7 @@ You'll learn to use MLflow for experiment tracking, build automated training pip
 </tr>
 <tr>
 <td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">Tools/tech stack</td>
-<td style="padding: 12px; border: 1px solid #dee2e6;">OpenAI API, LangChain, Hugging Face, Ollama, Qdrant, Elasticsearch</td>
+<td style="padding: 12px; border: 1px solid #dee2e6;">OpenAI API, minsearch, PGVector, Grafana, LangChain</td>
 </tr>
 <tr style="background-color: #f8f9fa;">
 <td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">Who it's for</td>
@@ -405,7 +405,7 @@ You'll learn to use MLflow for experiment tracking, build automated training pip
 
 [LLM Zoomcamp](https://datatalks.club/blog/llm-zoomcamp.html) is a free course on building AI systems with large language models (LLMs). Over 10 weeks, you learn how to create an AI application that answers questions from your own knowledge base, from foundational concepts and retrieval-augmented generation (RAG) to evaluation, optimization, and production deployment.
 
-The course covers both commercial APIs (OpenAI) and open-source models (Hugging Face, Ollama), teaches vector database integration with Qdrant and Elasticsearch, and shows you how to build production-ready RAG applications using LangChain. You'll also learn modern agent patterns, evaluation techniques, and how to integrate LLMs with external tools and APIs for real-world applications.
+The course covers managed LLM APIs (OpenAI), teaches you both text and vector search, and shows you how to build production-ready RAG applications. You'll also learn modern agent patterns, evaluation techniques, monitoring with Grafana, and how to integrate LLMs with external tools and APIs for real-world applications.
 
 <div style="text-align: center; margin: 2em 0;">
     <div style="display: inline-block; background: #28a745; padding: 0.5em 2em; border-radius: 8px; box-shadow: 0 4px 6px rgba(50, 50, 93, 0.11), 0 1px 3px rgba(0, 0, 0, 0.08); transition: all 0.15s ease;">
diff --git a/_posts/2024-11-11-llm-zoomcamp.md b/_posts/2024-11-11-llm-zoomcamp.md
@@ -13,7 +13,7 @@ tags:
 - artificial-intelligence
 - large-language-models
 title: 'LLM Zoomcamp: Free LLM Engineering Course and Certification'
-date: 2025-11-25
+date: 2026-05-11
 related_posts:
 - guide-to-free-online-courses-at-datatalks-club.html
 - data-engineering-zoomcamp.html
@@ -98,35 +98,35 @@ The course follows a practical, production-focused approach to building LLM appl
 <tr style="background-color: #f8f9fa;">
 <td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">2</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">Vector Search</td>
-<td style="padding: 12px; border: 1px solid #dee2e6;">Create embeddings, index documents, and retrieve with semantic search</td>
-<td style="padding: 12px; border: 1px solid #dee2e6;">Qdrant, dlt</td>
+<td style="padding: 12px; border: 1px solid #dee2e6;">Generate embeddings, index documents, and retrieve with semantic search</td>
+<td style="padding: 12px; border: 1px solid #dee2e6;">sentence-transformers, PGVector</td>
 </tr>
 <tr>
-<td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">2A</td>
-<td style="padding: 12px; border: 1px solid #dee2e6;">Agents (Bonus)</td>
-<td style="padding: 12px; border: 1px solid #dee2e6;">Add agentic behavior and function calling to RAG pipelines</td>
-<td style="padding: 12px; border: 1px solid #dee2e6;">OpenAI Function Calling</td>
+<td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">3</td>
+<td style="padding: 12px; border: 1px solid #dee2e6;">Agents</td>
+<td style="padding: 12px; border: 1px solid #dee2e6;">Add autonomous tool use and function calling to RAG pipelines</td>
+<td style="padding: 12px; border: 1px solid #dee2e6;">OpenAI Responses API, ToyAIKit</td>
 </tr>
 <tr style="background-color: #f8f9fa;">
-<td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">3</td>
+<td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">4</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">Evaluation</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">Measure retrieval quality and answer accuracy with offline and online evaluation</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">LLM-as-a-Judge, evaluation frameworks</td>
 </tr>
 <tr>
-<td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">4</td>
+<td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">5</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">Monitoring</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">Track user feedback, chat logs, and system performance in production</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">Grafana, monitoring dashboards</td>
 </tr>
 <tr style="background-color: #f8f9fa;">
-<td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">5</td>
+<td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">6</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">Best Practices</td>
-<td style="padding: 12px; border: 1px solid #dee2e6;">Optimize retrieval with hybrid search, reranking, and orchestration patterns</td>
-<td style="padding: 12px; border: 1px solid #dee2e6;">LangChain, hybrid search tools</td>
+<td style="padding: 12px; border: 1px solid #dee2e6;">Optimize retrieval with hybrid search and reranking</td>
+<td style="padding: 12px; border: 1px solid #dee2e6;">Hybrid search and reranking tools</td>
 </tr>
 <tr>
-<td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">6</td>
+<td style="padding: 12px; border: 1px solid #dee2e6; font-weight: 600;">7</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">End-to-End Project</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">Build a complete RAG application combining all components</td>
 <td style="padding: 12px; border: 1px solid #dee2e6;">All tools from previous modules</td>
@@ -139,7 +139,7 @@ The course follows a practical, production-focused approach to building LLM appl
 For the final project, you'll create a complete end-to-end RAG application. The goal is to show that you can move from raw data to a working, searchable AI system that users can interact with, and that you can evaluate and monitor.
 
 <figure>
-<img src="/images/posts/2024-11-11-llm-zoomcamp/llm-zoomcamp-fitness-assistant-project.png" alt="LLM Zoomcamp Fitness Assistant project - conversational AI RAG application helping users choose exercises and find alternatives for personalized fitness guidance" title="LLM Zoomcamp Fitness Assistant Project Example" loading="lazy" style="max-width: 100%; height: auto; border: 1px solid #ddd; border-radius: 4px;" />
+<img src="/images/posts/2024-11-11-llm-zoomcamp/llm-zoomcamp-course-project-example.png" alt="LLM Zoomcamp Fitness Assistant project - conversational AI RAG application helping users choose exercises and find alternatives for personalized fitness guidance" title="LLM Zoomcamp Fitness Assistant Project Example" loading="lazy" style="max-width: 100%; height: auto; border: 1px solid #ddd; border-radius: 4px;" />
 <figcaption><p>Example project: Fitness Assistant - a conversational AI that helps users choose exercises and find alternatives, making fitness more accessible for beginners who find gyms intimidating or lack access to personal trainers</p></figcaption>
 </figure>
 
@@ -201,15 +201,15 @@ Sharing your work online also helps you get noticed by social media algorithms,
 ### How to Get a Certificate
 
 <figure>
-<img src="/images/posts/2024-11-11-llm-zoomcamp/llm-zoomcamp-certificate.png" alt="LLM Zoomcamp certificate - free certificate for completing the LLM Zoomcamp course" title="LLM Zoomcamp Certificate" loading="lazy" style="max-width: 100%; height: auto; border: 1px solid #ddd; border-radius: 4px;" />
+<img src="/images/posts/2024-11-11-llm-zoomcamp/llm-zoomcamp-certificate.jpeg" alt="LLM Zoomcamp certificate - free certificate for completing the LLM Zoomcamp course" title="LLM Zoomcamp Certificate" loading="lazy" style="max-width: 100%; height: auto; border: 1px solid #ddd; border-radius: 4px;" />
 <figcaption><p>LLM Zoomcamp certificate for completing the course</p></figcaption>
 </figure>
 
 To receive a certificate, you'll need to complete the [final project](#what-youll-build-course-project) and peer review 3 other students' projects:
 
-1. **Complete the final project**: Build a real-world LLM application (RAG project) that demonstrates your mastery of all course concepts
-2. **Peer review**: Evaluate and provide feedback on 3 fellow students' projects during the peer review process
-3. **Submit on time**: Meet the project submission deadlines to qualify for certification
+1. Complete the final project: Build a real-world LLM application (RAG project) that demonstrates your mastery of all course concepts
+2. Peer review: Evaluate and provide feedback on 3 fellow students' projects during the peer review process
+3. Submit on time: Meet the project submission deadlines to qualify for certification
 
 
 ## What is DataTalks.Club Community?
@@ -224,7 +224,7 @@ DataTalks.Club has a supportive community of like-minded individuals in [our Sla
 
 ## How to Join LLM Zoomcamp
 
-You can join LLM Zoomcamp either by **following a live cohort** or **learning at your own pace**.
+You can join LLM Zoomcamp either by following a live cohort or learning at your own pace.
 
 All materials are freely available in the [LLM Zoomcamp GitHub repository](https://github.com/DataTalksClub/llm-zoomcamp). Each module has its own folder, and cohort-specific homework and deadlines are in the `cohorts` directory. Lectures are pre-recorded and available in this [YouTube playlist](https://www.youtube.com/playlist?list=PL3MmuxUbc_hIB4fSqLy_0AfTjVLpgjV3R).
 
@@ -269,6 +269,8 @@ When you join a live cohort, you get:
 > — [Vasiliy Chernykh](https://www.linkedin.com/in/v4siliy), LLM Zoomcamp course graduate ([Source](https://www.linkedin.com/posts/v4siliy_llm-machinelearning-ai-activity-7394774137300402177-dFY9))
 
 ## Frequently Asked Questions
+
+For more details about how our courses work, check the [Zoomcamp logistics guide](https://datatalks.club/docs/courses/zoomcamp-logistics/){:target="_blank"}. You can also find more information about this course in the [LLM Zoomcamp documentation](https://datatalks.club/docs/courses/llm-zoomcamp/){:target="_blank"}.
 {% include faq-accordion.html faqs=site.data.faqs.llm-zoomcamp %}
 
 <div style="text-align: center; margin: 2em 0;">
diff --git a/_posts/2025-09-23-ai-dev-tools-zoomcamp-2025-free-course-to-master-coding-assistants-agents-and-automation.md b/_posts/2025-09-23-ai-dev-tools-zoomcamp-2025-free-course-to-master-coding-assistants-agents-and-automation.md
@@ -6,7 +6,7 @@ authors:
 description: 'Free AI Dev Tools course: build projects with Copilot, Cursor, MCP, and n8n. Learn AI coding assistants, agents, CI/CD, and earn a certificate.'
 image: images/posts/2025-09-23-ai-dev-tools-zoomcamp-2025-free-course-to-master-coding-assistants-agents-and-automation/course-cover.png
 layout: post
-date: 2025-11-25
+date: 2026-05-11
 tags:
 - courses
 - artificial-intelligence
@@ -211,6 +211,8 @@ When you join a live cohort, you get:
 
 ## Frequently Asked Questions
 
+For more details about how our courses work, check the [Zoomcamp logistics guide](https://datatalks.club/docs/courses/zoomcamp-logistics/){:target="_blank"}.
+
 {% include faq-accordion.html faqs=site.data.faqs.ai-dev-tools-zoomcamp %}
 
 <div style="text-align: center; margin: 2em 0;">
