You'll get hands-on experience with TimescaleDB in this course, discovering how to upgrade PostgreSQL into an optimized time-series database. You will learn to optimize query speeds, drastically reduce storage footprints, and ensure your dashboards stay fast at scale.

Key concepts and hands-on projects include:

• Hypertables & Chunk Management
  Learn how TimescaleDB automatically partitions your data by time to speed up queries and streamline data retention without painful row deletions.

• Columnar Storage & Compression
  Discover how converting older row data into column-oriented batches can shrink your database size by over 90% and massively speed up analytical queries.

• Continuous Aggregates
  Stop recalculating identical data! You'll build incremental, automatically updating materialized views (and aggregate "ladders") that keep dashboards returning results in milliseconds.

• Hyperfunctions & Gap Filling
  Master specialized time-series functions for calculating percentiles, distinct counts, handling counter resets, and smoothing out data gaps for clean frontend charting.

• Data Tiering & Vector Search
  Explore moving older, cold data out of expensive local SSDs into cheaper S3 object storage seamlessly, and see how to combine standard time-series queries with AI vector search.

The course walks you through building two complete, production-ready projects from scratch:

1. An AI Agent Flight Recorder
   Track millions of language model inferences, tool calls, costs, and latencies locally in Docker.

2. An EV Charger Fleet Telemetry System
   Monitor 2,000 devices reporting every 10 seconds, deployed directly on the fully-managed Tiger Cloud platform.

Watch the full TimescaleDB Course on the freeCodeCamp.org YouTube channel (4-hour watch).