1. Home
  2. For developers
  3. SQL and databases
For developers · SQL and databases

AI for SQL developers and data engineers: your data is the context models work with

If you work with SQL, databases or data pipelines, you are already at the centre of AI systems, even if you have never written a prompt. RAG means retrieval over your data, vector search has entered PostgreSQL through pgvector, agents query databases through MCP tools, and evaluating a model starts with a clean golden dataset. Your relevance does not depend on learning machine learning, but on understanding how models consume data and what makes them give wrong answers.

Why you are relevant and where the risk is

Your advantage

AI projects that fail in production very often fail on data: badly indexed documents, permissions ignored at retrieval, schemas the model does not understand, evaluation sets that do not reflect reality. Someone who knows data modelling, data quality and controlled access solves exactly these problems, provided they also understand the other half: embeddings, chunking, hybrid search, structured outputs, evals.

Where the risk is

At the same time, models now generate queries, which changes who writes SQL. The need for SQL does not disappear; the monopoly on it does. Value moves towards designing schemas that models can use, validating what they generate and governing access: skills the courses below build on your foundation.

What changes in your work with SQL and databases

  1. Retrieval becomes a data problem

    Chunking, embeddings, vector indexing, hybrid filtering and permissions at row or document level. A RAG pipeline is, in essence, a data pipeline with a model stage at the end.

  2. Models write SQL, and someone has to validate it

    Generated queries reach products. The AI security course treats model output sent to a database as untrusted input, so clear schemas, parameterization, least-privilege access and validation before execution become the data team’s job.

  3. Databases are exposed to agents through MCP

    MCP servers for databases give agents access to schemas and queries. Least-privilege permissions, read-only resources, limits and audit are new requirements for whoever administers the data.

  4. Model quality is measured with datasets

    Golden datasets, human annotation, retrieval metrics and privacy rules for evaluation data. Evaluating AI systems is, to a large extent, data work done rigorously.

Each of these changes has at least one course in the track below. See the track

A Certificate of Completion for every course in the SQL and databases track

When you have gone through all the lessons of a course and have an average of at least 70% on its quizzes, you issue from your account, after confirming the conditions, a Certificate of Completion with a unique number and a public verification link. It is not issued automatically and it comes at no extra cost, with a plan or with single-course access.

  • Verifiable by anyone. Every certificate has a QR code and a public verification page, with its unique code. A recruiter checks it without an account.
  • With figures, not just a name. The percentage of lessons completed, the average quiz score and the study time are written on the document.
  • Three tiers, by quiz average: Pass (70–79%), Merit (80–89%) and Distinction (90% and above), shown on the document.
  • Your name, your choice. You decide whether your name appears on the public verification page, and you can change that choice at any time.
A sample certificate. The real document is a PDF, with a QR code and a public verification link.

AI courses for SQL and databases: 3 stages, 10 courses

In the order in which they matter. If you already have experience with model APIs, skip the foundations. For each course, the reason it matters to someone who works with SQL and databases.

  1. Stage 1: Foundations: how models consume data

    What an LLM is, how you talk to it, and the data engineering underneath every serious AI system.

    1. Introduction to AI Engineering 28 lessons · ~25 h Beginner

      LLMs, APIs, agents and evaluation: the complete frame, with a module on RAG, embeddings and vector databases that sets pgvector next to the dedicated engines.

      Key modules: Machine Learning Essentials · Large Language Models and Modern Architectures · Working with LLM APIs and Integrations · AI Tools for Developers

      Read the free preview Course details This course only: €99/month
    2. The Complete Prompt Engineering Masterclass 32 lessons · ~27 h Intermediate

      Prompt engineering for code, including a case study on optimising a slow SQL query, and prompt security: instructions that produce verifiable output and resist injection.

      Key modules: Advanced Prompting Techniques · Multi-Modal Prompt Engineering · Prompt Engineering for AI Agents · Prompt Engineering for Code

      Read the free preview Course details This course only: €99/month
    3. Data Engineering for AI: Pipelines, Vector Stores and Data Quality 31 lessons · ~26 h Advanced

      The course written for you: ingestion with change data capture, ETL and ELT with Airflow, Dagster and dbt, Parquet and Iceberg, data quality and contracts, embedding pipelines and vector databases in depth, with Python and SQL throughout.

      Key modules: Storage and Table Formats: Parquet and Iceberg · Ingestion from Diverse Sources · ETL/ELT and Orchestration · Data Quality, Validation, and Contracts

      Read the free preview Course details This course only: €99/month
  2. Stage 2: Systems: retrieval, context and controlled access

    The central skill: correct retrieval, with permissions, over relational data and documents.

    1. RAG: Retrieval-Augmented Generation in Practice 27 lessons · ~24 h Advanced

      Chunking, embedding models, hybrid search, re-ranking, advanced architectures and systematic evaluation: the pipeline of any AI system that answers from your data, with pgvector among the vector stores it covers.

      Key modules: Implementing the RAG Pipeline · Embedding Models and Document Processing · Advanced RAG · Advanced RAG Architectures

      Read the free preview Course details This course only: €99/month
    2. Context Engineering and Memory for AI Agents: Beyond Prompting 25 lessons · ~24 h Advanced

      Retrieval strategies for context, vector, graph, relational and hybrid, plus persistent memory and compaction: where data modelling decides the quality of an agent.

      Key modules: The Anatomy of Context: The Components of the Inference Window · Memory Types for AI Agents · Memory Managers and Persistence: Extraction, Consolidation, Store · Retrieval Strategies for Context: Vector, Graph, Relational, Hybrid

      Read the free preview Course details This course only: €99/month
    3. MCP (Model Context Protocol) — Building Servers and Integrations (Enterprise Edition) 22 lessons · ~25 h Advanced

      How data is exposed to agents: the schema as a read-only resource, the query as a parameterized tool, with validation against SQL injection, authentication and least-privilege permissions. The practical projects include a PostgreSQL server.

      Key modules: Building MCP Servers with Python · Building MCP Servers with TypeScript · Transport, Authentication and Configuration · Enterprise Patterns and Production Architectures

      Read the free preview Course details This course only: €99/month
    4. Build and Ship a Production AI SaaS: From Idea to Paying Users 30 lessons · ~25 h Advanced

      Postgres with pgvector as the product database, and multi-tenant isolation built on one rule: every row that belongs to a tenant carries a tenant id, and every query filters on it.

      Key modules: Choosing Your Stack: Frontend, Backend, and LLM APIs · Integrating the LLM: Streaming, Tools, and Cost Control · Vector Search and RAG for Your Product · Authentication and Multi-Tenancy

      Read the free preview Course details This course only: €99/month
  3. Stage 3: Operations: evaluation, lifecycle and data protection

    The stage where your data becomes the basis for the quality, compliance and safety of the AI system.

    1. LLM Evaluation and Testing: Shipping Reliable AI 30 lessons · ~25 h Advanced

      Golden datasets with edge cases and slices, human annotation, RAG metrics with Ragas and regression tests in CI/CD, with attention to privacy for evaluation data: evaluation as a data discipline.

      Key modules: Classic Metrics and Why They Fail on Open-Ended Text · LLM-as-a-Judge: Design, Bias and Calibration · Building Evaluation Datasets · The Evaluation Tooling Landscape

      Read the free preview Course details This course only: €99/month
    2. MLOps: The Machine Learning Lifecycle in Production 30 lessons · ~25 h Advanced

      Data and feature management with feature stores, training pipelines, data lineage and drift monitoring: the pipeline in which your data feeds and monitors models.

      Key modules: Experiment Tracking and Reproducibility · Data and Feature Management · Training Pipelines and Orchestration · Model Registry, Versioning, and CI/CD for ML

      Read the free preview Course details This course only: €99/month
    3. AI Security: Defending LLM Applications (OWASP LLM Top 10, Guardrails, Red-Teaming) 30 lessons · ~25 h Advanced

      PII, leakage and poisoning, the insecure handling of model output such as generated SQL, and the security of RAG pipelines: the requirements the data team will be asked to meet.

      Key modules: Prompt Injection: The Defining Threat · Insecure Output Handling and Downstream Exploits · Guardrails: Input and Output Filtering · Securing RAG and Agents: Excessive Agency

      Read the free preview Course details This course only: €99/month
All 25 IT courses, including the 10 in this track, in one plan. IT Pro: €399 per month, VAT included. Or only the course you are interested in, €99 per month, from the “This course only” link on each row.

The AI ecosystem around SQL and databases

What already exists, so that you do not start from zero. The courses in the track teach you what to build with it.

  • pgvector and vector search in SQL Embeddings stored and queried directly in PostgreSQL, next to relational data; the data engineering course has a full lesson on it.
  • Dedicated vector databases Pinecone, Qdrant and Weaviate for retrieval at scale, with approximate indexes and metadata filtering.
  • dbt, Airflow and Dagster Transformation and orchestration for the pipelines that feed models.
  • Parquet and Apache Iceberg Columnar storage and the table format behind a lakehouse.
  • MCP servers for databases Tools through which agents explore schemas and run queries, with the permissions and limits you configure.
  • Evaluation frameworks DeepEval, Ragas and promptfoo consume the test datasets you build and maintain like any other data asset.

What you will be able to do at the end of the SQL and databases track

  1. Design and evaluate a RAG pipeline over relational data and documents, with permissions at row or document level
  2. Add vector search in PostgreSQL or in a dedicated database, with hybrid filtering
  3. Build the ingestion, quality and embedding pipelines that feed models
  4. Expose databases to agents through MCP, with least-privilege permissions, limits and audit
  5. Build and maintain the evaluation datasets that decide the quality of the AI system

These are the skills you practise in the courses of the track; results depend on the time you invest and on your previous experience.

Start the SQL and databases track

What you get here that you do not get from a tutorial

Courses of about 25 hours, structured in modules

Code examples, architectures and case studies, and in some courses a capstone project at the end. Not summaries of documentation, but structured material that you go through in order, at your own pace.

AI Professor in every lesson

You ask in the context of the lesson, by typing or by voice, and get an explanation of the concept you are on. Every lesson has its quiz: about 354 questions per course on average. The professor is an AI system, not a human teacher, included in every plan with a fair-use limit.

Up to date with what the industry asks for

Agentic coding, MCP, RAG, agents, evals, LLM security, fine-tuning, AIOps, computer vision and Edge AI are whole courses in the catalog, not closing chapters.

See the material before you pay

A preview of the first lesson of every course can be read without an account. Then you choose a single course, €99 per month, or IT Pro, €399 per month, with the whole IT catalog. You can stop the renewal anytime from your account; access stays until the end of the period already paid for.

IT Pro opens all 25 IT courses, including the 10 in this track

The courses on this page are IT courses. With the IT Pro plan you have the whole IT catalog, the technical learning paths and the AI Professor; if you want only one course, you buy it separately.

One course

When you care about a single topic in the catalog

€ 99 per month, VAT included No commitment: stop the renewal anytime

about €4 per hour of course

1 course, your choice of 50 25 hours on average
  • All the course’s lessons, exercises and quizzes, about 354 questions per course on average
  • AI Professor in the lessons, included in your subscription
  • Publicly verifiable Certificate of Completion

IT Pro

Recommended

Developers, data engineers, architects. Code and production.

€ 399 per month, VAT included Billed monthly: stop the renewal anytime

€16 per month for each of the 25 courses

25 IT Pro courses 25 hours per course on average
  • Prompt engineering, LLMs, RAG, AI agents and MCP, Claude Code and Cursor, computer vision, MLOps, AI security
  • Hands-on projects with production examples
  • AI Professor in every lesson, quizzes and a certificate for every course

All Access

The whole catalog, both tracks side by side.

€ 499 per month, VAT included Billed monthly: stop the renewal anytime

€10 per month for each of the 50 courses

All 50 courses about 1,257 hours
  • You save €199 a month compared with the two bundles bought separately
  • Learning paths for both profiles
  • AI Professor in every lesson, quizzes and a certificate for every course

Subscriptions renew automatically; you can stop the renewal anytime from your account, and access stays until the end of the period already paid for. As digital content with immediate access, see the withdrawal conditions.

Compare all the plans · Plans for teams, by number of seats · Give a month of access as a gift

From the blog, for developers

Do you work in another language too?

The same skills, seen from each ecosystem. The languages close to SQL and databases are highlighted.

Questions about AI for SQL and databases

I am not an application developer but an analyst or a DBA. Does it make sense?

Yes. The courses are chosen for the data side of AI systems: pipelines, retrieval, schemas, evaluation, controlled access. You need Python at reading level for the examples; the introduction to AI engineering gives you the frame for the rest.

Is there SQL in the courses?

The data engineering course uses Python and SQL throughout, including in its lesson on pgvector. The MCP course builds a PostgreSQL server and treats the query as a parameterized tool. The other courses use Python, with SQL appearing where a database is involved.

Do models that generate SQL make my work pointless?

They change it. Models generate queries; someone has to design schemas they understand, validate what they produce, limit access and evaluate the results on known sets. Those are the skills the data engineering, MCP, security and evaluation courses build on your SQL foundation.

Which plan opens these courses?

All the courses recommended here are IT courses and open with the IT Pro plan, which includes every IT course in the catalog. It is billed monthly, and you can stop the renewal anytime from your account. There is also individual, monthly access to a single course. Every course has a free preview of its first lesson, readable without an account.

A free preview of the first lesson, without an account

Start the SQL and databases track today

10 courses, ~251 hours, opened with IT Pro: €399 per month, VAT included, with access to all 25 IT courses. The AI Professor is included in every plan.

Secure payment through Stripe Immediate access after payment Stop the renewal anytime

ChatGPT, OpenAI, Claude, Anthropic, Gemini, Google, Microsoft 365 Copilot, Cursor, Midjourney and the other product and company names mentioned are trademarks or trade names of their respective owners. Cursuri-AI.ro is an independent training provider and is not affiliated with, sponsored by or endorsed by any of them.

IT Pro: €399/month all 25 IT courses · VAT included
Choose IT Pro