🗄️ SQL Program – MAAB Academy

This repository contains materials from the MAAB Academy training program, focused on preparing students for careers in:

• Artificial Intelligence (AI)
• Machine Learning (ML)
• Deep Learning (DL)

This module is a continuation of the Python course and focuses on working with relational databases, transforming data, and preparing it for analytics and AI workflows.

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🎯 Program Mission

At MAAB Academy, our goal is to train highly skilled specialists who can:

• Work with real-world data
• Build data-driven solutions
• Prepare datasets for AI and Machine Learning models

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📚 SQL (Advanced – Continuation)

This stage develops strong SQL skills required for data analysis, data engineering, and AI pipelines.

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📌 Week 1–2: SQL Core Concepts

• Introduction to RDBMS: tables, primary/foreign keys, normalization
• Writing SELECT queries with filtering (WHERE)
• Sorting data using ORDER BY
• Using operators: BETWEEN, IN, LIKE
• Logical operators: AND, OR, NOT
• DISTINCT vs GROUP BY

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📌 Week 3–4: Data Aggregation & Joins

• Aggregate functions: COUNT(), SUM(), AVG(), MIN(), MAX()
• GROUP BY and HAVING
• Joins:
  • INNER JOIN
  • LEFT JOIN
  • RIGHT JOIN
  • FULL OUTER JOIN
• Combining multiple tables

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📌 Week 5: Advanced Queries

• Subqueries (nested, correlated)
• Common Table Expressions (CTEs) using WITH
• Conditional logic with CASE WHEN
• Handling NULL values: IS NULL, COALESCE, IFNULL

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📌 Week 6: Window Functions & Optimization

• Window functions:
  • ROW_NUMBER(), RANK(), DENSE_RANK(), NTILE()
• Analytical functions with OVER(PARTITION BY)
• Indexing basics
• Query optimization and execution plans

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📌 Week 7: Views & Stored Procedures

• Creating and using Views
• Writing Stored Procedures
• Working with Triggers and Transactions
• Error handling

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🚀 Final Project

• Work with a complex relational database
• Clean, transform, and aggregate data
• Deliver analysis-ready output for visualization and AI models

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🎯 Outcomes

By completing this module, students will:

• Write advanced SQL queries
• Work with relational databases efficiently
• Prepare clean datasets for analytics and AI
• Understand real-world data workflows