Sql For Newbies: Hands-On Sql With Industry Best Practices

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Sql For Newbies: Hands-On Sql With Industry Best Practices
Published 3/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.02 GB | Duration: 1h 33m

Beginner-friendly guide to writing, optimizing, and mastering SQL step by step!

[b]What you'll learn[/b]

Real-World Application & Optimization - Master industry-proven practices to optimize queries, enhance performance, and handle heavy data pipelines efficiently.

Learn in a hands-on onboarding setting, as if we're working side by side at the office, preparing you to manage upcoming requests.

Master the Fundamentals of SQL - Learn how to write basic SQL queries using SELECT, WHERE, CASE WHEN and ORDER BY to retrieve and filter data effectively.

Perform Data Aggregation & Analysis - Use SQL functions such as GROUP BY, HAVING, SUM(), COUNT(), and AVG() to summarize and analyze data.

Work with Multiple Tables & Optimize Queries - Understand different types of joins, use CTEs, and apply best practices for query optimization.

Leverage Advanced SQL Features - Explore window functions (ROW_NUMBER(), PARTITION BY, LEAD(), LAG()), date manipulation and data transformations

[b]Requirements[/b]

No programming experience needed.

[b]Description[/b]

In this hands-on guide, you'll dive into SQL with real-world insights and industry best practices used by top professionals. You'll learn how to optimize queries, enhance performance, and manage data like a pro. Picture us working side by side in the office, with me guiding you through every concept step-by-step. No prior experience required! This course is perfect for beginners, and by the end, you'll confidently work with databases and have a strong foundation to boost your career.What you'll cover:Basic SQL Queries - Write your first queries with SELECT, WHERE, JOIN, and more.Data Aggregation - Use GROUP BY, HAVING, SUM(), and COUNT() to summarize and analyze data.Advanced SQL Features - Learn about window functions, CTEs, and query optimization.Real-World Examples - Work on practical tasks like optimizing queries and handling large datasets.Best Practices - In the "Work Smarter, Not Harder" lecture, discover market-proven tips to create optimal queries and efficient tables that will save you time and effort.Final Assignment:As your final challenge, you'll tackle the project Optimizing a Public Transport Analytics Pipeline, where you'll design an optimized table to analyze key metrics for a public transport authority. This will help you develop the skills needed to work with real data in a business context.With multiple hands-on exercises throughout the course, you'll have all the tools you need to confidently apply SQL in your career. Start today and unlock new career opportunities!

Overview

Section 1: Welcome to SQL Land

Lecture 1 Introduction

Lecture 2 Lecture 2: What's a Relational Database Anyway?

Lecture 3 Lecture 3: The SQL Toolbox

Section 2: Introduction to Basic Statements

Lecture 4 How To Use SELECT statement

Lecture 5 How To Use WHERE statement

Lecture 6 How To Use CASE WHEN statement

Lecture 7 How To Use ORDER BY statement

Section 3: Intro to Aggregations

Lecture 8 How To Use GROUP BY statement

Lecture 9 How To Use HAVING statement

Section 4: Joining Tables

Lecture 10 Type of Joins

Lecture 11 How To Use INNER JOIN

Lecture 12 How To Use LEFT JOIN

Lecture 13 How To Use RIGHT JOIN

Lecture 14 How To Use FULL OUTER JOIN

Section 5: Common Table Expressions (CTEs)

Lecture 15 Lecture: CTEs And How To Structure A Query

Section 6: Window Functions

Lecture 16 Window Functions ROW NUMBER(), LEAD(), LAG() PARTITION BY

Section 7: Building Efficient SQL Pipelines

Lecture 17 Work Smarter, Not Harder: Market-Proven Tips for Optimal Queries & Tables

This course is suitable for absolute beginners who want to learn SQL from scratch. It's ideal for: Aspiring entry level data analysts, data scientists, or database administrators who want to build a foundation in SQL. Professionals in non-technical roles looking to work with data more effectively. Students or career changers exploring data-related fields.

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