Mastering Postgres | The most comprehensive course on PostgreSQL
Course description
Your application operates at the speed of the slowest query, regardless of the language, framework, or platform you use. The course "Mastering Postgres" is a comprehensive video course that will help you improve your applications and career.
You will gain a deep understanding of the core principles of PostgreSQL through real-life examples. You will learn about the various data types that Postgres offers, when it's best to use them, and more importantly, when not to use them. You will understand how indexes work, learn to improve them, and maintain your database at peak performance.
"Mastering Postgres" is the best way to learn Postgres and enhance your applications and career. The course covers everything from fundamental principles to advanced topics like indexes and data types.
Learn the Basics, Master the Complexities
Start with basic knowledge and gradually move on to complex topics, including indexing and working with various data types.
Become a Full-Text Search Master
Learn how to use Postgres's full-text search capabilities to create powerful search functions.
Become an Index Expert
Indexes are key to fast queries. Learn how to create and use them to speed up database performance.
Your application will operate only as fast as your slowest query, regardless of the language, framework, or platform. This course will help you gain deeper insight into PostgreSQL through real-life examples, enhance indexing, and keep your database performing at its best.
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| # | Title | Duration |
|---|---|---|
| 1 | Introduction to the course | 02:15 |
| 2 | Overview of course structure | 03:41 |
| 3 | Postgres vs. everyone | 02:09 |
| 4 | The psql CLI | 02:39 |
| 5 | Introduction to schema | 06:46 |
| 6 | Integers | 09:40 |
| 7 | Numeric | 09:51 |
| 8 | Floating point | 08:05 |
| 9 | Storing money | 08:17 |
| 10 | NaNs and infinity | 03:45 |
| 11 | Casting types | 05:36 |
| 12 | Characters types | 07:43 |
| 13 | Check constrai | 08:55 |
| 14 | Domain types | 07:49 |
| 15 | Chars and collations | 07:48 |
| 16 | Binary data | 09:01 |
| 17 | UUIDs | 06:20 |
| 18 | Boolean | 03:48 |
| 19 | Enums | 12:45 |
| 20 | Timestamps | 12:44 |
| 21 | Timezones | 13:13 |
| 22 | Dates and times | 07:51 |
| 23 | Intervals | 05:47 |
| 24 | Serial type | 09:53 |
| 25 | Sequences | 04:50 |
| 26 | Identity | 07:03 |
| 27 | Network and mac addresses | 04:49 |
| 28 | JSON | 10:18 |
| 29 | Arrays | 07:05 |
| 30 | Generated columns | 08:03 |
| 31 | Text search types | 07:43 |
| 32 | Bit string | 05:16 |
| 33 | Ranges | 15:40 |
| 34 | Composite types | 04:20 |
| 35 | Nulls | 03:53 |
| 36 | Unique constrai | 05:38 |
| 37 | Exclusion constrai | 06:52 |
| 38 | Foreign key constrai | 10:51 |
| 39 | Introduction to indexes | 05:28 |
| 40 | Heaps and CTIDs | 04:18 |
| 41 | B-Tree overview | 05:02 |
| 42 | Primary keys vs. secondary indexes | 03:01 |
| 43 | Primary key types | 07:13 |
| 44 | Where to add indexes | 08:45 |
| 45 | Index selectivity | 09:16 |
| 46 | Composite indexes | 08:45 |
| 47 | Composite range | 03:09 |
| 48 | Combining multiple indexes | 04:34 |
| 49 | Covering indexes | 08:54 |
| 50 | Partial indexes | 06:30 |
| 51 | Index ordering | 04:01 |
| 52 | Ordering nulls in indexes | 02:36 |
| 53 | Functional indexes | 05:23 |
| 54 | Duplicate indexes | 03:05 |
| 55 | Hash indexes | 04:13 |
| 56 | Naming indexes | 02:17 |
| 57 | Introduction to explain | 01:25 |
| 58 | Explain structure | 05:17 |
| 59 | Scan nodes | 11:29 |
| 60 | Co and rows | 08:24 |
| 61 | Explain analyze | 02:39 |
| 62 | Introduction to queries | 01:26 |
| 63 | Inner joins | 06:19 |
| 64 | Outer joins | 05:41 |
| 65 | Subqueries | 06:38 |
| 66 | Lateral joins | 06:23 |
| 67 | ROWS FROM | 03:45 |
| 68 | Filling gaps in sequences | 06:56 |
| 69 | Subquery elimination | 14:21 |
| 70 | Combining queries | 07:58 |
| 71 | Set generating functions | 06:22 |
| 72 | Indexing joins | 04:47 |
| 73 | Introduction to advanced SQL | 01:26 |
| 74 | Cross joins | 05:21 |
| 75 | Grouping | 11:08 |
| 76 | Grouping s, rollups, cubes | 07:15 |
| 77 | Window functions | 18:11 |
| 78 | CTEs | 10:31 |
| 79 | CTEs with window functions | 10:35 |
| 80 | Recursive CTE | 06:45 |
| 81 | Hierarchical recursive CTE | 06:20 |
| 82 | Handling nulls | 06:51 |
| 83 | Row value syntax | 11:44 |
| 84 | Views | 07:44 |
| 85 | Materialized views | 10:53 |
| 86 | Removing duplicate rows | 05:01 |
| 87 | Upsert | 08:38 |
| 88 | Returning keyword | 04:00 |
| 89 | COALESCE + generated column | 04:32 |
| 90 | Introduction to full text search | 03:01 |
| 91 | Searching with LIKE | 03:04 |
| 92 | Vectors, queries, and ranks | 08:10 |
| 93 | Websearch | 05:56 |
| 94 | Ranking | 14:10 |
| 95 | Indexing full text search | 06:09 |
| 96 | Highlighting | 03:32 |
| 97 | Intro to JSON | 03:16 |
| 98 | JSON vs JSONB | 04:17 |
| 99 | Validating JSON | 04:42 |
| 100 | Creating JSON objects + arrays | 08:21 |
| 101 | JSON extraction | 08:25 |
| 102 | JSON containment | 04:15 |
| 103 | JSON existence | 03:04 |
| 104 | JSON recordset | 08:42 |
| 105 | Updating JSON | 11:54 |
| 106 | Indexing JSON parts | 10:09 |
| 107 | GIN index | 06:15 |
| 108 | Intro to pgvector | 02:18 |
| 109 | Vector embedding columns | 08:00 |
| 110 | Find related articles | 09:22 |
| 111 | Upsert vector embedding | 03:02 |
| 112 | Semantic search | 05:36 |
| 113 | Other operators | 03:06 |
| 114 | Vector indexes | 05:00 |
| 115 | Thank you | 01:42 |
| 116 | Heroku's glory days & Postgres vs the world (with Craig Kerstiens) | 01:02:46 |
| 117 | Creating a Postgres platform with Monica & Tudor from Xata.io | 01:01:21 |
| 118 | Bootstrapping an email service provider (with Jesse Hanley) | 01:21:58 |
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