SQL and Advanced Queries | AIML End-to-End Session 58

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Artificial Intelligence
Machine Learning (AIML)?

Welcome to Session 58 of our End-to-End AIML series! In this session, we explore Advanced SQL Queries that go beyond basic data retrieval and manipulation, empowering data scientists to handle complex data analysis tasks efficiently.

What You'll Learn:

Advanced SQL Techniques for Data Science:
Complex JOINs: Master advanced JOIN operations, including SELF JOIN, CROSS JOIN, and complex multi-table joins to combine data from various sources.
Subqueries and Nested Queries: Learn how to write subqueries and nested queries to extract more granular insights from your datasets.
Window Functions in Depth: Dive deeper into window functions such as LAG, LEAD, and RANK for sophisticated data analysis tasks.
Common Table Expressions (CTEs): Simplify complex queries and improve query readability with recursive CTEs and multi-level CTEs.
Advanced Aggregations: Perform advanced aggregations and create custom metrics using HAVING and GROUP BY clauses.
Pivoting Data: Learn how to pivot your data in SQL, transforming rows into columns for easier analysis.
Optimization Techniques: Explore query optimization strategies like using indexes, EXPLAIN plans, and query caching to improve query performance.
Real-World Use Cases: See how advanced SQL queries can be used for data cleaning, ETL processes, and machine learning feature engineering.
Hands-On Coding Example: Watch step-by-step examples of how advanced SQL queries are written and applied to real-world data science tasks.
Best Practices: Discover tips for optimizing complex queries, handling large datasets, and ensuring your SQL code is efficient and scalable.
By the end of this session, you will have mastered advanced SQL querying techniques, giving you the tools to tackle complex data science challenges with confidence.

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