SQL, or Structured Query Language, is a programming language that allows users to communicate with and manipulate databases. With the increasing importance of data and the rise of big data, SQL skills are becoming more and more valuable in today’s job market. Whether you are a data analyst, a data scientist, or a software developer, having a strong understanding of SQL can help you work more efficiently and better use of data.
If you’re looking to improve your SQL skills, there are a variety of courses available that can help you. Here are 10 SQL courses that can help you boost your database skills.
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1. Introduction to Structured Query Language (SQL)
In this course, you will walk through the steps of installing a text editor, installing MAMP or XAMPP (or equivalent), and creating a MySql database. You will learn about single-table queries and basic SQL syntax, multi-table database design, foreign keys, and JOIN operations. Finally, you will learn to model many-to-many relationships, such as those needed to represent users, roles, and courses.
What’s Skills You Will Learn
PHPMyAdmin
MySQL
Relational database
SQL
2. Introduction to SQL for BigQuery and Cloud SQL
This is a self-contained lab that takes place in the Google Cloud Console.
In this lab, you’ll learn basic SQL clauses and get hands-on practice running structured queries in BigQuery and Cloud SQL.
In this project you will:
- Identify the various components and hierarchies in the BigQuery console.
- Create a new instance of Cloud SQL and load the exported CSV file as a new table.
- Execute CREATE DATABASE, CREATE TABLE, DELETE, INSERT INTO, and UNION queries in Cloud SQL.
What’s Skills You Will Learn
- CloudSQL
- Database management
- Data operations
- Structured Data Sets
- SQL
3. Foundations for Big Data Analysis with SQL
This course provides an in-depth look at using SQL for Big Data, starting with an overview of data, database systems, and Common Query Language (SQL). You will then learn about Big Data specific features and SQL tools for working on Big Data platforms. You will also install the practice environment (virtual machine) used in the advanced course and have the opportunity to do initial database and spreadsheet exploration in this environment.
At the end of the course, you will be able to
• Distinguish between operational and analytical databases and understand how they apply to Big Data;
• understand how database and table design provides a structure for working with data;
• Assess how differences in data volume and diversity influence the choice of appropriate database systems;
• recognize the characteristics and advantages of SQL dialects designed to work with big data systems for storage and analysis; And
• Explore databases and tables in big data platforms.
WHAT YOU WILL LEARN
- Distinguish between operational and analytical databases and understand their relationship to big data
- Understand how database and table designs provide structure for working with data
- Evaluate how differences in data volume and variety affect the choice of a suitable database system
- Get to know the capabilities and benefits of an SQL dialect designed to work with big data systems for storage and analysis
4. Analyzing Big Data with SQL
This course gives you an in-depth look at SQL SELECT statements and their basic clauses. This course focuses on the Apache Hive and Apache Impala big data SQL engines, but most of the information also applies to SQL using traditional RDBM; the lecturer specifically discusses the differences between MySQL and PostgreSQL.
At the end of the course, you will be able to
• Search and navigate databases and spreadsheets using various tools;
• understand the basics of a SELECT statement;
• understand how and why results are filtered;
• Exploring clustering and aggregation to answer analytical questions;
• Work by sorting and narrowing results; And
• Combine multiple tables in different ways.
WHAT YOU WILL LEARN
- Understand the basics of SELECT statements
- Find out how and why results are filtered
- Examine clustering and aggregation to answer analytical questions
- Work by sorting and narrowing the results
5. Managing Big Data with MySQL
This course is an introduction to using relational databases in business analysis. You’ll learn how a relational database works and how to use an object relation diagram to show the structure of the data stored in it. This knowledge will help you understand how data should be collected in a business context and help you identify features to consider when engaging in implementing new data collection efforts. You will also learn how to run the most useful reports and query aggregation tables for business analysts and practice using them with real databases. You no longer have to wait 48 hours for someone else in the company to give you data – you can retrieve the data yourself!
What’s Skills You Will Learn
- Data analysis
- MySQL
- Terada
- SQL
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6.SQL for Data Science
As data collection has grown exponentially, so has the need for people experienced in using and interacting with data; can think critically and provide insight to make better decisions and optimize their business. These are data scientists, “part mathematicians, part computer scientists, and part trend watchers” (SAS Institute, Inc.). According to Glassdoor, data scientist is the best job in America; with an average base salary of $110,000 and thousands of positions open at once. One of the skills a good data scientist needs is the ability to extract and work with data, and to do that you need to be proficient in SQL, the standard language for communicating with database systems.
This course is designed to introduce you to the basics of SQL and working with data so you can start analyzing it for data science purposes. You’ll start asking the right questions and finding good answers to provide valuable information for your business. This course starts with the basics and assumes you have no prior knowledge or knowledge of SQL.
What’s Skills You Will Learn
- Identify the necessary subsets of data for the column or set of columns and write SQL queries to constrain those results.
- Use SQL commands to filter, sort, and summarize data.
- Create analysis tables from multiple queries using the UNION operator.
- Manipulate string, date, and numeric data using functions to integrate data from multiple sources into fields in the right format for analysis.
7. Scripting with Python and SQL for Data Engineering
In this third Python, Bash, and SQL Foundations course for Data Engineering Specialization, you will learn techniques for working effectively with Python and SQL. We’ll go through useful data structures in Python scripts and connect to databases like MySQL. You will also learn how to use modern text editors to connect and execute SQL queries with real databases and perform data loading and fetching operations. Lastly, they use data retrieved from websites using scraping techniques. These skills enable you to work effectively when data is not available or spatial queries are required to extract useful information from databases.
What’s Skills You Will Learn
- Extract data from multiple sources and map it to Python data structures.
- Design a script to connect and query SQL databases from within Python.
- Apply extraction techniques to read and extract data from websites.
8.SQL for Data Science with R
Most of the world’s data reside in databases. SQL (or Structured Query Language) is a powerful language used to communicate with and retrieve data from databases. Knowledge of databases and SQL is a must if you want to become a data scientist.
The aim of this course is to introduce relational database concepts and to help you learn and apply basic knowledge of SQL and R languages.
The emphasis in this course is on hands-on, hands-on learning. That way, you’re working with real databases, real data science tools, and real data sets.
What’s Skills You Will Learn
- Create and access database instances in the cloud
- Create and execute basic SQL statements – SELECT, INSERT, UPDATE, DELETE, CREATE, DROP
- Create SQL statements to filter, sort, and group results, use built-in functions, create nested queries, and access multiple tables
- Analyze Jupyter data with R and SQL, combining SQL and R skills to query real-world data sets
9. Microsoft Azure SQL
In this course, you will learn the basics of database concepts in a cloud environment, gain basic knowledge of cloud data services, and build your basic knowledge of cloud data services in Microsoft Azure. You will explore relational data offerings, provision and deploy relational databases, and query relational data through data cloud solutions using Microsoft Azure. You will learn that you will learn about SQL. You will see how it is used to query and maintain data in databases and the various dialects available.
This is the second course in a five-course program designed to help you prepare for the DP-900 Exam: Microsoft Azure Data Fundamentals. so you can demonstrate that you have a basic understanding of basic database concepts in a cloud environment.
What’s Skills You Will Learn
Describe the properties of relational data
Describe the types of nonrelational and NoSQL databases
Define a non-relational data type
Select the most appropriate relational data loading suggestion
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10. Oracle SQL Basics
This course, Oracle SQL Fundamentals, is the third course in the Oracle Specialization. It is designed to help you learn the key elements of the Oracle-specific Structured Query Language.
We recommend that you complete the first two courses (Oracle Database Foundations and Oracle Database Platform) before starting this course.
