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AI SQL Developer

The “AI SQL Developer” training is a practical course showing how to use AI in daily work with Microsoft SQL Server without relinquishing control over your code.

Duration
24h · 3 days
Ask about the program → See all
Who it's for

Ideal for teams that…

1 People working with Microsoft SQL Server
2 People who know basic SQL / T-SQL
3 Programmers who want to increase productivity when working with SQL
4 Developers focused on query performance and architecture who want to significantly increase their work effectiveness
Outcomes after the program

Hands-on AI and data analytics workshops — built around your team's real cases.

✓

Implementation, analysis, and refactoring of SQL / T-SQL queries with AI assistance, including detecting syntax, logic and semantic errors

✓

Debugging code, writing procedures, functions, views, and analyzing side effects of queries

✓

Using AI for code review, refactoring, and simplifying existing code — eliminating unnecessary JOINs and repeated conditions

✓

Writing queries faster while maintaining full control and making conscious decisions about readability vs performance

✓

Translating complicated SQL into business language and recognizing incorrect or unsafe AI suggestions

✓

Conscious and safe use of AI in working with databases

Requirements

What you should know before we start

  • Access to ChatGPT, preferably at least the “GO” version
  • Knowledge of relational database concepts and basics of SQL / T-SQL
  • Familiarity with the Windows environment
Program · 8 modules

What we actually do

M01
AI as a database developer tool
  • · What AI is in the context of working with SQL / T-SQL
  • · What AI is not in this context
  • · AI as assistant, consultant, and code reviewer
  • · Typical AI applications in SQL / T-SQL work
  • · AI limitations — key aspects
  • · When AI should not be trusted
  • · Module summary
M02
Preparing the work environment
  • · Creating a database for training
  • · Preparing tables and data
M03
AI as part of the SQL developer workflow
  • · AI in SQL Server Management Studio (SSMS)
  • · Working with various SQL artifacts
  • · Safety in AI usage — a critical aspect
  • · Building context for queries for AI
  • · AI-assisted workflow model
  • · Module checklist as training material
M04
Practical introduction to AI – ChatGPT
  • · What AI (Artificial Intelligence) is
  • · How AI works
  • · Pattern of a correct prompt
M05
Finding and analyzing SQL / T-SQL errors
  • · Why SQL debugging is challenging
  • · Types of SQL and T-SQL errors
  • · Syntax errors
  • · Logic errors
  • · Semantic errors
M06
Writing SQL and T-SQL queries with AI assistance
  • · Why AI is good for writing SQL
  • · AI as pair programmer model
  • · Generating SELECT queries with AI
  • · Generating JOIN with AI
  • · GROUP BY and HAVING with AI support
  • · CTE (Common Table Expressions)
  • · Subqueries — generation and refactoring
  • · Writing stored procedures with AI
  • · Writing functions with AI
  • · Views — generation and organization
  • · AI as first-draft query generator
  • · Validating AI-generated queries
  • · Checklists for this module
M07
SQL / T-SQL code refactoring
  • · What code refactoring is
  • · What SQL / T-SQL refactoring is
  • · Simplifying SQL / T-SQL queries
  • · Eliminating unnecessary JOINs
  • · Eliminating repeated conditions
  • · Changing subqueries to CTE
  • · Changing CTE to JOIN
  • · Standardizing T-SQL style
  • · Readability vs performance — architectural decisions
  • · Refactoring model with AI
  • · Module checklists
M08
Translation and analysis of queries
  • · Introduction to code review
  • · Why reading SQL / T-SQL is harder than writing it
  • · Analyzing business logic of queries
  • · Analyzing side effects of queries
  • · Translating SQL into natural language
  • · Translating natural language into SQL
  • · Working with someone else’s code — why it’s difficult
  • · Ideal applications of this module
  • · Analysis with AI model
Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.
How we work

From brief to retro in 30 days.

01

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

02

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

03

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

04

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

Send a brief. We'll reply within 1 day.

After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.

✓Quote within 48h of the brief
✓First session within 30 days
✓Pilot before the full decision
✓VAT invoice, payment in instalments possible

How we handle your data

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