SQL FOR DATA SCIENCE AND ANALYTICS

Categories: Databases
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About Course

Data lives in databases. This course shows you how to actually work with it.

You will learn SQL from the ground up, then move quickly into the kind of queries used in real data and engineering roles. Instead of isolated examples, the course is built around practical scenarios that reflect what analysts, engineers and data scientists deal with every day.

You will:

  • Write queries to clean messy data, join multiple tables, and extract meaningful patterns.
  • Learn how to aggregate data, work with time-based records, and handle edge cases that usually break simple queries.
  • Write complex SQL will feel natural, not forced.

There is a strong focus on thinking, not memorizing. You will understand why a query works, how to optimize it, and how to debug it when things go wrong. You will also see how SQL fits into a broader data workflow, including how it supports dashboards, reports, and machine learning pipelines.

If you want to move beyond basic SELECT statements and start solving real problems with data, this course gives you that foundation.

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What Will You Learn?

  • Write SQL queries to extract and analyze data from real-world databases
  • Understand how relational databases are structured and how tables connect through keys and relationships
  • Filter and retrieve precise datasets using SELECT, WHERE, and logical conditions
  • Combine data from multiple tables using different types of JOINs
  • Break down complex problems using subqueries and step-by-step logic
  • Summarize data using aggregation functions like COUNT, SUM, and AVG
  • Transform and classify data using CASE statements and conditional logic
  • Organize complex queries into cleaner steps using Common Table Expressions (CTEs)
  • Perform advanced analysis using window functions like ranking and running totals
  • Develop a practical SQL mindset that helps you solve real data science and analytics problems

Course Content

Course Introduction and SQL Installation Guide.
This section sets the foundation for the course and gets your environment ready. You will start with a clear overview of what the course covers, how it is structured, and what you should expect to be able to do by the end. It also explains how SQL fits into data science and analytics workflows, so you understand why you are learning it and where it will be applied. From there, you will go through a step by step setup of MySQL on your system. The process is broken down to avoid common installation issues, with guidance on configuration and basic setup. By the end of this section, you will have a working database environment and be ready to start writing queries immediately.

  • Understanding Databases and Their Role in Data Science and Analytics.
    01:02:50
  • MySQL Setup and Practice Database Installation
    01:02:50
  • Database Creation and Management Fundamentals
    01:02:50
  • Database Fundamentals and MySQL Setup Quiz

Fundamentals of Querying Databases.
This topic introduces the core skill of working with data in a database: writing queries. You will learn how to retrieve data using SQL, starting from simple SELECT statements and gradually building toward more structured filtering and extraction. The focus is on understanding how to ask precise questions of a database and get meaningful results back. You will explore how to filter rows, select specific columns, and control what data is returned. The topic also introduces the mindset behind querying, which is thinking in terms of conditions, structure, and logic rather than manual searching. By the end, you should be comfortable extracting data from a database and understanding how queries form the foundation of every analysis workflow.

Intermediate SQL Concepts.
This topic moves you beyond single-table queries into more realistic data problems where information is spread across multiple tables. You will learn how to use JOINs to combine related data from different tables. This includes understanding how relationships between tables are defined and how to retrieve meaningful results by linking them together. You will work with common join types and see how each one affects the output of a query. You will also explore subqueries, which allow you to write queries inside other queries. This helps you break down complex problems into smaller steps and is often used for filtering, aggregation, and conditional logic. By the end of this topic, you should be able to handle multi-table queries confidently and structure more advanced SQL logic for real-world analytics problems.

Advanced SQL Concepts: CTEs and Window Functions.
This topic introduces advanced SQL techniques used in real-world analytics and complex data processing. You will learn how to use Common Table Expressions (CTEs) to structure queries in a clearer and more modular way. CTEs help you break down complex logic into readable steps, making large queries easier to write, debug, and maintain. You will also explore window functions, which allow you to perform calculations across sets of rows while still retaining row-level detail. Unlike traditional aggregation, window functions let you compute running totals, rankings, and moving averages without collapsing your data. By the end of this topic, you should be able to write more structured and powerful SQL queries that handle advanced analytical tasks efficiently and cleanly.

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