Drift audit fixes: nav text, index card descriptions

apartsin · claude · apartsin · commit e67be141fed1 · 2026-04-05T13:35:21.000+03:00
Fix Appendix T section link text mismatch in appendix-u/index and
capstone/requirements (was "Production Data Pipelines..." but actual
title is "Ray Train, Ray Serve, and Ray Data"). Update chapter index
cards for sections 12.5, 19.4, 20.6 to reflect content that was
moved within those sections.

Co-Authored-By: Claude Opus 4.6 &lt;noreply@anthropic.com&gt;
diff --git a/appendices/appendix-u-docker-containers/index.html b/appendices/appendix-u-docker-containers/index.html
@@ -72,7 +72,7 @@ <h2>Sections</h2>
     </ul>
 
     <nav class="chapter-nav">
-    <a class="prev" href="../appendix-t-distributed-ml/section-t.5.html">Production Data Pipelines and Model Serving at Scale</a>
+    <a class="prev" href="../appendix-t-distributed-ml/section-t.5.html">Ray Train, Ray Serve, and Ray Data</a>
     <a class="up" href="../../toc.html">Appendices</a>
     <a class="next" href="section-u.1.html">Docker Fundamentals: Images, Containers, and Volumes</a>
 </nav>
diff --git a/capstone/requirements.html b/capstone/requirements.html
@@ -10,7 +10,7 @@
 <body>
 
 <nav class="chapter-nav">
-    <a class="prev" href="../appendices/appendix-t-distributed-ml/section-t.5.html">Production Data Pipelines and Model Serving at Scale</a>
+    <a class="prev" href="../appendices/appendix-t-distributed-ml/section-t.5.html">Ray Train, Ray Serve, and Ray Data</a>
     <a class="up" href="../toc.html">Table of Contents</a>
     <a class="next" href="index.html">Capstone Project</a>
 </nav>
diff --git a/part-3-working-with-llms/module-12-hybrid-ml-llm/index.html b/part-3-working-with-llms/module-12-hybrid-ml-llm/index.html
@@ -134,7 +134,7 @@ <h3>Learning Objectives</h3>
                 <span class="section-desc">
                     NER, relation extraction, and event extraction with LLMs. Classical IE pipelines
                     (spaCy, CRF) vs. LLM-based extraction. Structured output with BAML, Instructor,
-                    and Pydantic. Hybrid IE patterns and production deployment.
+                    and Pydantic. Keyword/keyphrase extraction and LLM-powered AutoML.
                 </span>
             </a>
         </li>
diff --git a/part-5-retrieval-conversation/module-19-embeddings-vector-db/index.html b/part-5-retrieval-conversation/module-19-embeddings-vector-db/index.html
@@ -129,8 +129,8 @@ <h3>Learning Objectives</h3>
                 <span class="section-desc">
                     Document loaders and parsing. Chunking strategies: fixed-size, recursive,
                     semantic, and structure-aware. Overlap and parent-child retrieval.
-                    Unstructured.io, LlamaParse, Docling. RAG ETL pipelines, document versioning,
-                    and incremental indexing.
+                    Unstructured.io, LlamaParse, Docling. Topic modeling with LLM embeddings,
+                    RAG ETL pipelines, and incremental indexing.
                 </span>
             </a>
         </li>
diff --git a/part-5-retrieval-conversation/module-20-rag/index.html b/part-5-retrieval-conversation/module-20-rag/index.html
@@ -149,8 +149,8 @@ <h3>Learning Objectives</h3>
                 <span class="section-title">RAG Frameworks &amp; Orchestration</span>
                 <span class="section-desc">
                     LangChain (chains, retrievers, LCEL). LlamaIndex (index types, query engines).
-                    Haystack pipelines. Comparing frameworks for different RAG use cases.
-                    Production deployment patterns and evaluation.
+                    Haystack pipelines. Compound AI systems and DSPy.
+                    RAG security, poisoning attacks, and production deployment.
                 </span>
             </a>
         </li>
