The 10 best SQL courses in 2026

Build production-ready data pipelines using Delta Live Tables and the Medallion Architecture on Databricks. This hands-on course teaches you to design, implement, and monitor ETL workflows that transform raw data into reliable, business-ready datasets through a structured bronze-silver-gold layering pattern. This course is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with professionals with an interest in programming. You will start by mastering DLT fundamentals — declarative pipeline syntax in both SQL and Python, streaming ingestion w

Modern marketing analytics requires more than dashboards you need the ability to access and shape raw data. In Query Your Data: SQL for the AI Era, you’ll learn how to use SQL and AI tools together to extract, analyze, and validate marketing data across multiple sources. You’ll start by understanding how marketing data is structured across tables such as sessions, events, ads, and CRM records. You’ll learn how to use SQL joins to connect these sources and create campaign-level views that link ad spend to revenue outcomes. Rather than writing every query from scratch, you’ll focus on promptin

AWS: Databases Course is the fourth course of Exam Prep DVA-C02: AWS Certified Developer Associate Specialization. This course assists learners in learning the core concepts of NoSQL, contrasting it with traditional SQL databases. It covers key aspects of DynamoDB, including compute capacity, read consistency, transactions, and streams. The course also explores other NoSQL options like Amazon MemoryDB for Redis, covering cluster setup, data loading, and its comparison with ElastiCache for Redis. Finally, it provides an overview of Amazon RDS, a managed relational database service. This cours

In Data Cleaning, Transformation, and Manipulation, you’ll learn to turn messy data into analysis- and modeling-ready datasets using Python (pandas) and SQL. This is a skill-based path organized around real workplace tasks. Each module mirrors responsibilities you see in job descriptions and focuses on the exact steps you’ll perform on the job. You’ll begin with a quick skills check, then personalize your journey: double down on new topics, or skip what you already know. For each skill, you’ll review concise lessons curated from expert instructors with explanations and demos for filtering and

University of Michigan's beginner-friendly path covering Python programming, data structures, web data, and databases.

Learn SQL with PostgreSQL — queries, joins, aggregation, and database design.

Google's job-ready data analytics path: spreadsheets, SQL, Tableau, R, and data storytelling.

Python, SQL, data analysis, visualization, machine learning, and a capstone project.

Learn Python, Django, APIs, and databases to start a career as a back-end developer.

Advanced PostgreSQL: schema design, indexes, transactions, and performance tuning.