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

From SQL Basics to Modern Analytics with Polars – Hands-On Data Skills for 2025

What you'll learn
- Learn strategies to optimize memory usage and processing speed when dealing with massive datasets.
- Master Subqueries & Common Table Expressions (CTEs) – Break down complex problems into manageable, efficient queries.
- Solve Real-World Data Challenges – Work on practical, project-based problems that mimic real business scenarios.
- Taking advantage of parallel and optimised analysis with Polars
- 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.

Requirements
- No prior experience is required! This course is designed for beginners, Basic knowledge of Python & SQL is good to have, and I'll guide you step by step. All you need is a computer with an internet connection and a willingness to learn."

Description
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 botheagerandlazyAPIs

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 onSQL 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.

Who this course is for:
- This course is perfect for beginners who want to learn SQL analysis from scratch. Whether you're a student, a working professional, or simply curious about SQL analysis, this course will provide you with a solid foundation. No prior experience is required!
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