Udemy - Databricks Certified Context Engineering Associate

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Udemy - Databricks Certified Context Engineering Associate (Size: 2 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Introduction
  1. Introduction.mp4 9.5 MB
  10 - Conclusion
  2 - CHAPTER 0 SETUP
  10. LOCAL_instructions_of_use.pdf 104 KB
  10. Local VScode Instructions of Use.html 5.5 KB
  2. Chapter presentation.mp4 18.9 MB
  3 - CHAPTER I CONTEXT ENGINEERING FOUNDATIONS
  11. Chapter presentation.mp4 7.1 MB
  12. Effective context engineering for AI agents.url 102.4 B
  12. What is context engineering.mp4 22.6 MB
  13. Unified and open governance for data and AI.url 102.4 B
  13. Unity Catalog.mp4 75.5 MB
  13. What is Unity Catalog.url 102.4 B
  14. MLflow 3 docs on Databricks.url 102.4 B
  14. MLflow.mp4 53.6 MB
  15. Lakebase Autoscaling overview. Databricks docs.url 102.4 B
  15. Lakebase.mp4 14.6 MB
  15. Postgres compatibility (PG16, params, pg_stat_statements). Databricks docs.url 102.4 B
  15. Synced tables reverse ETL (Delta → Lakebase). Databricks docs.url 102.4 B
  15. What is pgvector (positioning operational vs. lakehouse). Databricks blog.url 102.4 B
  16. Anthropic — Extended thinking.url 102.4 B
  16. Build agent.mp4 76.6 MB
  16. Effective Context Engineering for AI Agents. Anthropic Engineering.url 102.4 B
  17. Drew Breunig — How contexts fail and how to fix them.url 102.4 B
  17. Drew Breunig — How to fix your context.url 102.4 B
  17. Failure modes & context strategies.mp4 53.1 MB
  17. Less is More — dynamic tool selection (Berkeley FCL).url 102.4 B
  4 - CHAPTER II SYSTEM PROMPT & INSTRUCTION DESIGN
  18. Chapter presentation.mp4 6.2 MB
  19. Genie space.mp4 98.4 MB
  20. Prompt engineering overview.url 102.4 B
  20. Prompt.mp4 104.2 MB
  21. Few-shot selection.mp4 54.4 MB
  22. Token tradeoff.mp4 40.8 MB
  5 - CHAPTER III KNOWLEDGE RETRIEVAL & GENIE CONFIGURATION
  23. Chapter presentation.mp4 12.7 MB
  24. RAG (Retrieval Augmented Generation) on Databricks.url 102.4 B
  24. RAG introduction.mp4 7.8 MB
  25. Build an unstructured data pipeline for RAG.url 102.4 B
  25. RAG workflow.mp4 89.5 MB
  26. Chunking.mp4 68.3 MB
  26. Chunking.url 102.4 B
  27. Vector Search.mp4 68.8 MB
  28. Genie space curation.mp4 23.7 MB
  29. UC metadata diagnosis.mp4 33.9 MB
  30. RAG pipeline.mp4 66.3 MB
  30. ai_parse_document function.url 102.4 B
  31. Vector search diagnosis.mp4 51.6 MB
  6 - CHAPTER IV MEMORY ARCHITECTURE WITH LAKEBASE & MLFLOW
  32. Chapter presentation.mp4 7.2 MB
  33. AI agent memory. Databricks docs.url 102.4 B
  33. Agent state and memory (Lakebase). Databricks docs.url 102.4 B
  33. Lakebase architecture.mp4 18.1 MB
  34. Agent state and memory (Lakebase). Databricks docs.url 102.4 B
  34. Memory Retrieval Quality & Context Integrity.mp4 25.7 MB
  35. Create lakebase endpoint.mp4 13.8 MB
  36. AI agent memory (Model Serving).url 102.4 B
  36. Short memory agent.mp4 61.9 MB
  7 - CHAPTER V TOOL DESIGN, MCP & AGENT CONTEXT
  37. Chapter presentation.mp4 12 MB
  38. AI agent Tools.url 102.4 B
  38. Agent tools.mp4 67.5 MB
  38. Model Context Protocol (MCP) on Databricks.url 102.4 B
  39. Create tools.mp4 112.1 MB
  40. Connect GitHub MCP.mp4 67.6 MB
  40. Install an external MCP.url 102.4 B
  41. Progressive disclosure.mp4 56.6 MB
  42. Agent layered MCP.mp4 14.9 MB
  43. Context pruning.mp4 31.8 MB
  8 - CHAPTER VI CONTEXT COMPRESSION & COMPACTION
  44. Chapter presentation.mp4 5.8 MB
  45. Compaction. Claude Developer Platform.url 102.4 B
  45. OpenAI Compaction.url 102.4 B
  45. What is compaction.mp4 55.2 MB
  46. Compaction - Hands-on.mp4 42.8 MB
  9 - CHAPTER VII MULTI-AGENT & LONG HORIZON TASK DESIGN
  47. Chapter presentation.mp4 5.6 MB
  48. Anthropic — How we built our multi-agent research system.url 102.4 B
  48. Databricks Supervisor Agent.url 102.4 B
  48. Multi-agent Failure.mp4 93.8 MB
  3. Databricks Free Edition limitations.url 102.4 B
  3. Databricks Free Version.mp4 5.9 MB
  3. Free Edition.url 102.4 B
  3. Sign up for Databricks Free Edition.url 102.4 B
  4. Connect GitHub to Databricks.mp4 48.2 MB
  4. GitHub Repos.url 102.4 B
  5. Get API Key.url 102.4 B
  5. Get a Claude API key.mp4 15.7 MB
  5. Get started with Claude.url 102.4 B
  6. Create & Manage LLM Credentials.mp4 33.4 MB
  7. Create a Claude Serving Endpoint.mp4 35.6 MB
  8. Create a PDF Volume.mp4 58.7 MB
  9. Create Delta table from CSV.mp4 101.9 MB
  49. Conclusion.mp4 4.1 MB

Description


Databricks Certified Context Engineering Associate
https://WebToolTip.com
Published 7/2026

Created by olivier AUFFRET

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Level: Intermediate | Genre: eLearning | Language: English | Duration: 49 Lectures ( 5h 39m ) | Size: 2.1 GB
How do you optimize LLM inputs ?
What you'll learn

⚡ Navigate the databricks GenAI ecosystem

⚡ Diagnostic and solve GenAI context issues.

⚡ Prepare the Databricks Context Engineer Associate Certification

⚡ Fill a context window without 'context rot'.
Requirements

❗ Basic Python programming

❗ Familiarity with SQL

❗ A general understanding of what large language models (LLMs) are

❗ A GitHub account

❗ No prior Databricks experience required

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