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DataEngineering

Data Engineering With AI

Learn how AI is transforming modern data engineering with automated pipelines, intelligent data quality checks, AI-powered ETL, cloud analytics, and faster data workflows using tools like Python, SQL, Snowflake, BigQuery, and Apache Spark.

4.6 (1463)10,663 learners25 lessons2h 0m

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Curriculum

Topic

  • AI Is Transforming Data Engineer Roles: What’s Changing4:58
  • The Data Engineer Role Just Split Into 4 Jobs — Which One Are You?4:19
  • Writing SQL Is No Longer the Hardest Part of Being a Senior Data Engineer — Here’s What Is4:34
  • Chunking Is the New Partitioning — The Data Engineering Decision That Makes or Breaks RAG4:40
  • Fixed vs Recursive vs Semantic Chunking — Choosing the Right Strategy for Your AI Pipeline4:26
  • Embedding Pipelines Explained — How Data Engineers Choose & Version Embedding Models6:03
  • Your embedding model just got upgraded — how to re-embed billions of rows without downtime7:01
  • CDC for Unstructured Data — The Ingestion Pattern Most Data Pipelines Miss4:27
  • Vector Indexes for Data Engineers — HNSW vs IVF vs Flat Without the Math Degree8:17
  • Pure Vector Search Is Dead — Why Hybrid Retrieval Is Now the Production Standard9:51
  • Rerankers — The Low-Cost Pipeline Upgrade That Beats Bigger Embedding Models5:22
  • Query Transformation as a Pipeline Stage — Rewriting Vague Questions Before Retrieval3:56
  • Your RAG Gave a Wrong Answer — The Data Engineer’s Failure Tree for Debugging It2:48
  • PDFs Are the New CSVs — Building Parsing Pipelines That Scale to Millions5:18
  • The Duplicate Documents Secretly Killing Your Data Quality — MinHash, SimHash & Embedding Dedup Explained3:47
  • The 5 AI Agents Every Self-Healing Data Pipeline Needs4:33
  • Schema Drift That Fixes Itself — Letting AI Patch Your Pipeline Without a Ticket4:04
  • Stop Measuring Uptime — The New SLA Every Senior Data Engineer Is Moving To4:30
  • LangGraph + Airflow — The Production AI Agent Pattern Data Teams Are Shipping5:11
  • How I Built a Complete Data Engineering Pipeline from a Teams Message Using Claude Code2:22
  • 12-Month Legacy Migration Done in 6 Weeks — The AI-Driven Playbook for Data Teams4:01
  • Let Claude Write the Data Engineering Tests You Forgot — Prompt Patterns That Actually Work4:07
  • Natural Language to SQL in Production — 3 Wins and 3 Disasters3:48
  • Your Data Passed Every Test and Is Still Wrong — Semantic Data Validation Explained3:30
  • Your LLM Bill Is About to Explode — Token Budgets as a First-Class Pipeline SLI4:29
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