Data Analysis: Advanced SQL, 1000x Faster Python & Visualize

SQL (Structured Query Language) is the industry-standard language for managing and analyzing data stored in relational databases. Whether you are a data analyst, business intelligence professional, marketer, product manager, student, or someone pivoting into tech, learning SQL can unlock the potential to extract meaningful insights from data.

This course is designed to take you from the very basics of SQL to advanced techniques used in real-world data analysis. No prior programming or database experience is required. You'll learn by doing—writing SQL queries against real datasets and solving analytical problems that reflect practical scenarios.

By the end of the course, you will not only understand how SQL works, but more importantly, you will be able to use it to answer complex business questions, clean and transform data, and create data-driven reports.

What You'll Learn

This course is structured to help you gradually build your skills, layer by layer, with a focus on analysis:

Getting Started with SQL

• What is SQL and why it matters in data analysis

• Understanding databases, tables, rows, and columns

• Setting up your SQL environment (we will use a browser-based tool for easy access)

• Writing your first SQL query

Core SQL Skills

• Selecting data using the SELECT statement

• Filtering results with WHERE conditions

• Using comparison and logical operators

• Sorting and limiting data using ORDER BY and LIMIT

• Working with NULL values and handling missing data

Data Aggregation and Grouping

• Counting, summing, averaging, and finding min/max values

• Grouping data with GROUP BY

• Filtering aggregated results with HAVING

• Calculating percentages and ratios from grouped data

Joining Tables

• Understanding relationships between tables

• Inner joins, left joins, right joins, and full outer joins

• Combining data from multiple tables to form complete views

• Join best practices and avoiding common pitfalls

Data Cleaning and Transformation

• Using CASE statements for conditional logic

• Working with text using functions like UPPER, LOWER, SUBSTRING, REPLACE

• Working with dates and times: extracting year, month, weekday

• Removing duplicates with DISTINCT

• Data type conversions and formatting

Advanced SQL for Analysis

• Subqueries: writing queries within queries

• Common Table Expressions (CTEs) for readable and reusable SQL

• Window functions (ROW_NUMBER, RANK, LEAD, LAG) for advanced analysis

• Analytical functions to calculate running totals, rolling averages, and more

• Using COALESCE and NULLIF for data management

Real-World Analytical Scenarios

• Cohort analysis to study user behavior over time

• Funnel analysis for product and marketing optimization

• Retention analysis and churn measurement

• Sales and revenue trends using time series SQL

• Customer segmentation based on behavior and attributes

Polars: The Next-Gen DataFrame Library

• Introduction to Polars: Series, DataFrames, expressions, and lazy execution

• Learn how Polars differs from Pandas—and why it's faster

• Perform data cleaning, filtering, aggregation, and joins

• Explore both eager and lazy APIs

• Apply Polars in real-world analytical workflows

SQL + Polars: Hybrid Workflows

• When to use SQL, when to use Polars—and how to use them together

• Import data from PostgreSQL into Polars

• Build complete data pipelines for analysis and reporting

• Answer complex business questions using both tools

• Create reproducible analysis in Jupyter Notebooks

  
  

  
  

Why This Course?

There are many SQL courses out there. This one is different because it focuses specifically on SQL for analysis, not just learning the syntax. You won’t be building or administering databases; instead, you’ll focus on asking and answering questions with data.

Whether you want to become a data analyst, prepare for interviews, or simply level up your analytical thinking, this course is built for you. It’s clear, practical, and based on real problems—not academic exercises.

Who Is This Course For?

This course is for anyone who wants to develop strong SQL skills for analyzing data. You do not need a computer science background or prior programming experience.

This includes:

• Aspiring data analysts or data scientists

• Business analysts and marketing professionals

• Product managers and operations managers

• University students and career switchers

• Professionals who work with Excel and want to transition to databases

• Anyone curious about how data analysis is done in the real world

All examples and projects use easy-to-understand datasets and are explained step-by-step, so even complete beginners can follow along.

Outcomes and Benefits

By the end of this course, you will:

• Be able to write clean and efficient SQL queries

• Understand how to connect multiple tables and extract meaningful insights

• Know how to clean, filter, and transform data for reporting

• Be comfortable performing analytical tasks like segmentation, trends, and cohort analysis

• Build confidence to apply for data roles that require SQL

• Add a highly marketable skill to your resume or portfolio

Whether you are preparing for a data analyst interview or looking to improve your decision-making with data, SQL is a critical skill that will serve you across industries.

What You Will Receive

• Over 9 hours of video content

• Downloadable notebooks and SQL scripts

• Real datasets from different domains (sales, users, marketing, products)

• Practice exercises and quizzes to test your knowledge

• Certificate of completion

• Lifetime access to course materials and future updates

• Dedicated Q&A support to assist you on your journey

Final Note

Learning SQL is one of the smartest investments you can make in your career. It opens doors to roles in data, analytics, and technology, and it empowers you to make data-informed decisions wherever you are.

This course takes a practical, hands-on approach to mastering SQL for analysis—so that by the time you finish, you’re not just someone who knows SQL, but someone who can use SQL to think analytically and drive action through data.

Join today and take the first step toward becoming fluent in the language of data.