Master AI-First Data Engineering in 6 Interactive Lessons
Build modern data pipelines where AI and LLMs are first-class citizens — semantic ingestion, vector-native storage, hybrid retrieval, and agentic orchestration. Learn the exact foundation that powers production RAG and agents — with step-by-step walkthroughs written so a beginner can follow along. No videos required.
The Complete Curriculum
6 lessons covering everything from the AI-first data stack to observable production pipelines. Each lesson includes interactive walkthroughs with real commands.
The AI-First Data Stack
Understand the shift from traditional ETL to AI-first pipelines built for semantic search, RAG, and agents. Learn the five-layer architecture, chunking strategy, vector storage, and serving agents and RAG.
Building a Semantic Ingestion Pipeline
Build a pipeline that ingests documents, chunks them, embeds each chunk, and loads vectors into a vector database. Ingest a PDF, clean text, chunk with overlap and metadata, generate embeddings, and upsert vectors.
Vector Database Selection & Indexing
Compare vector databases, configure HNSW/IVF indexes, and benchmark query latency. Initialize a collection, configure HNSW parameters, load 100k vectors, and compare recall vs. speed.
Metadata Filtering & Hybrid Search
Combine vector similarity with metadata filters and keyword search for high-precision retrieval. Add metadata, run filtered vector search, combine with BM25, fuse with reciprocal rank, and measure precision.
Pipeline Orchestration & Observability
Orchestrate ingestion jobs, monitor embedding costs, and trace retrieval for debugging. Schedule nightly jobs, track token usage, log retrievals, set alerts, and generate data freshness reports.
AI-First Data Engineering Flashcards
Master the core concepts of AI-first data pipelines — semantic chunking, embeddings, vector databases, HNSW, hybrid search, and metadata filtering.
Real Tools You'll Master
These are the exact vector databases and techniques used by AI-first data engineers in production.
Prove Your Skills with Real-World Capstones
After completing the lessons, tackle 3 capstone projects: an enterprise semantic knowledge base, a hybrid retrieval system, and an observable AI data platform. Each capstone is a multi-step challenge with no answer keys — just like the real job.
View Capstone ProjectsFrequently Asked Questions
Do I need prior data engineering experience to take this course?
Some familiarity with Python and data pipelines helps, but Lesson 1 starts with the fundamentals — the shift from traditional ETL to AI-first pipelines and the five-layer architecture. Every lesson includes step-by-step walkthroughs written so a beginner can follow along.
What vector databases does this course cover?
Pinecone, Weaviate, pgvector, and Milvus. You'll compare them, configure indexes (HNSW and IVF), and benchmark query latency so you can choose the right one for your scale.
Is this course free?
Yes. The Master AI-First Data Engineering course is available on the free Initiate tier. You can start Lesson 1 immediately — no credit card required.
Will this help me build RAG and agentic systems?
Yes. You'll build the data foundation that RAG and agents depend on — semantic ingestion, vector storage, hybrid retrieval, and observable pipelines. Bad retrieval is the #1 cause of bad AI output, and this course fixes that.
How is this different from video-based training?
Instead of passively watching videos, you read interactive walkthroughs with real commands you follow along with. Research shows interactive text-based learning improves retention over passive video watching.
Will this help me get a job as an AI data engineer?
The course teaches the exact skills AI-first data engineers use daily: semantic ingestion, vector databases, hybrid search, and pipeline observability. Combined with the resume builder and blockchain-verified credentials, you'll arrive at interviews with real knowledge.
Ready to Build AI-First Data Pipelines?
Start your first lesson today — free. Every completed lab earns a blockchain-verified Proof-of-Hack credential employers can verify instantly.
Start the Course