Introduction to SQL
Learn how to create and query relational databases using SQL in just two hours.
Learn how to create and query relational databases using SQL in just two hours.
Accompanied at every step with hands-on practice queries, this course teaches you everything you need to know to analyze data using your own SQL code today!
Level up your SQL knowledge and learn to join tables together, apply relational set theory, and work with subqueries.
Master the complex SQL queries necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in PostgreSQL.
Learn how to explore what's available in a database: the tables, relationships between them, and data stored in them.
Learn to design databases in SQL to process, store, and organize data in a more efficient way.
Learn how to create one of the most efficient ways of storing data - relational databases!
Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon!
Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.
Learn how to analyze a SQL table and report insights to management.
Learn to use SQL Server to perform common data manipulation tasks and master common data manipulation tasks using this database system.
Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.
In this course, you will use T-SQL, the flavor of SQL used in Microsoft's SQL Server for data analysis.
Learn to write SQL queries to calculate key metrics that businesses use to measure performance.
Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.
Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.
In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.
Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.
Master SQL Server programming by learning to create, update, and execute functions and stored procedures.
In this course, students will learn to write queries that are both efficient and easy to read and understand.
Learn how to create a PostgreSQL database and explore the structure, data types, and how to normalize databases.
Explore ways to work with date and time data in SQL Server for time series analysis
Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.
Learn the most important functions for manipulating, processing, and transforming data in SQL Server.
Learn how to structure your PostgreSQL queries to run in a fraction of the time.
Develop the skills you need to clean raw data and transform it into accurate insights.
Learn how to write recursive queries and query hierarchical data structures.
Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.
Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.
Learn how to design and implement triggers in SQL Server using real-world examples.
Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.
Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.
Master Amazon Redshift's SQL, data management, optimization, and security.
Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.
Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.
In this course, you'll learn the basics of relational databases and how to interact with them.
This course will take you from Snowflake's foundational architecture to mastering advanced SnowSQL techniques.
Learn to manipulate and analyze flexibly structured data with MongoDB.
This course introduces dbt for data modeling, transformations, testing, and building documentation.
Improve your Python data importing skills and learn to work with web and API data.
Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.
Identify issues in a manufacturing process using SQL window functions and subqueries
Use SQL to figure out the golden era of video games!
Write SQL queries to answer interesting questions about international debt using data from The World Bank.
Use your data manipulation skills to perform exploratory data analysis on a dataset around student mental health.
Use your Intermediate SQL skills to explore a dataset about product carbon emissions.
Use skills gained in the Data Analyst in SQL career track to derive insights about motorcycle part sales over time across multiple warehouse sites!
Use your SQL skills to find out how many companies reached a valuation of over $1 billion across different industries between 2019 and 2021!
Use categorization and ranking techniques to explore 101 years of American baby name tastes.
Use joining techniques to discover the oldest businesses in the world.
Use SQL to analyze a database containing information about Transport for London journeys over 12 years!
Use SQL to analyze a database containing information about Transport for London journeys over 12 years!
Use SQL to analyze a database containing information about Transport for London journeys over 12 years!
Analyze UEFA Champion's League Soccer Games using Snowflake SQL.
Test your Data engineering skills by creating a data pipeline to analyze E-commerce business of Walmart!