Master Sql For Data Analysis: From Beginner To Advanced

Learn SQL from scratch for data analysis, BI, and data science. Write queries, optimize, and work with cloud databases!

What you'll learn

Master SQL for Data Analysis – Follow a structured, hands-on approach to transform raw data into meaningful insights.

Solve Real-World Data Challenges – Work on practical, project-based problems that mimic real business scenarios.

Write Powerful SQL Queries for Data Manipulation – Learn to extract, filter, aggregate, and transform complex datasets efficiently.

Unlock the Power of Joins & Multi-Table Analysis – Master INNER, LEFT, RIGHT, FULL, SELF, and CROSS JOINs to combine data like a pro.

Analyze Trends with Window Functions – Use RANK, LAG, LEAD, NTILE, and more to perform advanced data analysis.

Optimize Performance for Big Data – Learn best practices for indexing, query tuning, and handling millions of records with ease.

Master Subqueries & Common Table Expressions (CTEs) – Break down complex problems into manageable, efficient queries.

Requirements

This course is suitable for all learners and no knowledge required and who want to strengthen their skills and prepare for Data Analysis.

Description

Master SQL for Data Analysis: From Beginner to AdvancedThis course has been completely designed from the ground up to give you a comprehensive, hands-on learning experience in SQL for data analysis. Whether you’re a beginner with no prior experience or someone looking to enhance your SQL and data analytics skills, this course will take you through everything from fundamental queries to advanced SQL techniques used by data analysts, data scientists, and business intelligence professionals.If you’ve ever wanted to extract meaningful insights from data, but felt overwhelmed by databases, this course is for you! We take a practical, step-by-step approach, ensuring that you don’t just learn SQL—you master it.Why Learn SQL for Data Analysis?SQL is one of the most in-demand skills for data analysts, data scientists, and business intelligence professionals. Companies like Google, Netflix, Amazon, Airbnb, and Facebook use SQL to extract insights, analyze trends, and make data-driven decisions.This course focuses not just on writing queries, but also on real-world applications, including data visualization, performance tuning, and cloud-based SQL environments like Snowflake, BigQuery, and PostgreSQL.What You’ll Learn:SQL Basics: Build a Strong FoundationUnderstand relational databases and how SQL works.Learn to write queries, retrieve data, and filter results.Use WHERE, ORDER BY, and LIMIT to refine your queries.Data Analysis with SQL: Aggregations & ReportingGroup and summarize data with GROUP BY and HAVING.Use aggregate functions like SUM, AVG, COUNT, MIN, and MAX to analyze datasets.Perform advanced filtering and sorting to extract meaningful insights.Mastering SQL Joins & SubqueriesLearn INNER, LEFT, RIGHT, and FULL OUTER JOINS to combine data from multiple tables.Work with subqueries and Common Table Expressions (CTEs) to break down complex queries.Advanced SQL Techniques: Analytics & Performance OptimizationMaster Window Functions like RANK, LEAD, LAG, NTILE, and DENSE_RANK for time-series and ranking analysis.Use CASE statements, COALESCE, and NULL handling for data transformation.Optimize queries with indexes, query execution plans, and performance tuning.Python + SQL: The Best of Both WorldsLearn how to connect SQL with Python’s Pandas library for data manipulation.Extract, clean, and visualize SQL data using Python and Pandas.Build automated reporting pipelines with Python and SQL.Real-World Projects & Hands-On LearningThis course is packed with hands-on exercises, coding challenges, and real-world projects that will reinforce your learning. You will apply your SQL skills to:By the end of this course, you’ll have a portfolio of SQL projects to showcase your expertise!Who is This Course For?     spiring Data Analysts & Data Scientists looking for hands-on SQL experience.     Business & Marketing Professionals who want to analyze and visualize company data.     Python Users who want to integrate SQL with Pandas for data analysis.     Developers & Engineers who want to write better, optimized SQL queries.     Anyone who wants to master SQL for real-world data analysis!What Makes This Course Different?     Engaging & Hands-On – This isn't just another theory-based course! You’ll write SQL queries within minutes and work on real-world projects.     Project-Based Learning – Apply what you learn immediately with practical exercises and data analysis case studies.     Clear & Structured Approach – No fluff, just step-by-step guidance from SQL basics to advanced analytics.     SQL + Python Integration – Future-proof your learning by connecting SQL with Python’s Pandas for advanced data analysis.     Real-World Applications – Master SQL for business intelligence, data science, and analytics roles.By the End of This Course, You Will:     Write and optimize SQL queries like a pro.     Analyze data efficiently using SQL’s powerful functions.     Integrate SQL with Python Pandas for in-depth analysis.     Work with real-world datasets and gain hands-on experience.     Build a strong SQL portfolio with multiple projects.This isn’t just another course where you watch me code for hours—it’s an interactive learning experience that will empower you to work confidently with SQL and data analysis.So, let’s get started! Enroll today and start mastering SQL for Data Analysis!

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Database Quickstart

Lecture 2 Installation: Mac

Lecture 3 Installation: Windows

Section 3: Database & Schema

Lecture 4 Database Operations

Section 4: Tables

Lecture 5 Create Base Tables

Lecture 6 Insert into Tables

Lecture 7 Create and Drop Tables

Section 5: Basics

Lecture 8 Select Columns

Lecture 9 Experiments: Select

Lecture 10 Experiments: Select 2

Lecture 11 Experiments: Select (Without Tables)

Lecture 12 Experiments: Mathematical Expression

Lecture 13 Distinct

Lecture 14 Experiments: Distinct

Lecture 15 Key Takeaways: Distinct

Lecture 16 Aggregate Functions

Lecture 17 Key Takeaways: Aggregate Functions

Lecture 18 Customer and Orders: Select

Section 6: String Functions

Lecture 19 String Functions

Lecture 20 Sub-Strings

Lecture 21 Concat

Lecture 22 Key Takeaways: String Functions

Lecture 23 Length

Section 7: Limiting Records

Lecture 24 Limit & Offset

Lecture 25 Key Takeaways: Limit & Offset

Section 8: Alias

Lecture 26 Alias

Lecture 27 Key Takeaways: Alias

Section 9: Filters

Lecture 28 Filters with Numeric

Lecture 29 Key Takeaways: Numeric

Lecture 30 Filters with String

Lecture 31 Key Takeaways: String

Lecture 32 Filters with Date

Lecture 33 Key Takeaways: Date

Lecture 34 Filters with Boolean

Lecture 35 Key Takeaways: Boolean

Lecture 36 IN Clause

Lecture 37 Experiments: IN

Lecture 38 Key Takeaways: IN

Lecture 39 Between

Lecture 40 Key Takeaways: Between

Lecture 41 Like

Lecture 42 Experiments: Like

Lecture 43 Key Takeaways: Like

Section 10: Changing Data Types

Lecture 44 Cast: Decimal & Integers

Lecture 45 Key Takeaways: Cast

Section 11: Handling Data

Lecture 46 Default Values

Lecture 47 Handling Null

Section 12: Data Analysis

Lecture 48 Case: Conditional Functions

Lecture 49 Coalesce

Lecture 50 Null IF

Section 13: Keys & Constraints

Lecture 51 Keys: Primary, Foreign & Composite Key

Lecture 52 Constraints: Unique

Lecture 53 Constraints: Check

Section 14: Sub-Queries

Lecture 54 Inner Queries

Lecture 55 Experiments: Inner Queries

Section 15: Union & Intersect

Lecture 56 Union

Lecture 57 Experiments: Union

Lecture 58 Union All

Lecture 59 Experiments: Union All

Lecture 60 Intersect

Section 16: Group By

Lecture 61 Group By

Lecture 62 Group By with Having

Lecture 63 Group By with Filters

Lecture 64 Experiments: Group By

Section 17: Sorting: Order By

Lecture 65 Order By

Lecture 66 Order By with Filters

Section 18: Joins

Lecture 67 Introduction: Inner Join

Lecture 68 Example: Inner Join

Lecture 69 Introduction: Left Join

Lecture 70 Example: Left Join

Lecture 71 Example: Right Join

Section 19: Views

Lecture 72 Views

Lecture 73 Experiments: Views

Lecture 74 Materialized: Views

Section 20: Data Manipulation Language

Lecture 75 Insert Rows

Lecture 76 Update Rows

Lecture 77 Delete Rows

Lecture 78 Alter Tables

Section 21: Temporary Tables

Lecture 79 Temp Tables

Section 22: Functions - UDFs

Lecture 80 User Defined Functions

Section 23: SQL with Python

Lecture 81 Mac: Python Installation

Lecture 82 Python - SQL Connectivity

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