Comprehensive MySQL Course for All Levels

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Comprehensive MySQL Course for All Levels

Inbox Learners Hub's MySQL course offers in-depth tutorials and hands-on practice in database management and SQL syntax. Boost your career with essential database skills.

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  • 3500.00₹
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Course Content

11 sections • 25 lectures • 01h 23m total length
MySql - DDL
In the context of database management and SQL (Structured Query Language), MySQL DDL (Data Definition Language) statements fall under the broader category of "Database Management" or "Database Operations." Specifically, DDL refers to the subset of SQL statements used to define the structure of databases and database objects such as tables, indexes, views, and schemas. DDL statements in MySQL include commands like CREATE, ALTER, DROP, TRUNCATE, and RENAME, among others. These statements are essential for creating and modifying the structure of databases and their components, ensuring data integrity, and managing data definitions efficiently.
06:11min
Create Table
In the context of database management and SQL (Structured Query Language), MySQL DDL (Data Definition Language) statements fall under the broader category of "Database Management" or "Database Operations." Specifically, DDL refers to the subset of SQL statements used to define the structure of databases and database objects such as tables, indexes, views, and schemas. DDL statements in MySQL include commands like `CREATE`, `ALTER`, `DROP`, `TRUNCATE`, and `RENAME`, among others. These statements are essential for creating and modifying the structure of databases and their components, ensuring data integrity, and managing data definitions efficiently. Understanding MySQL DDL is crucial for database administrators and developers tasked with designing and maintaining databases, as it forms the foundation for organizing and manipulating data within MySQL databases effectively.
03:40min
Insert Data
In SQL databases such as MySQL, inserting data into a table is a fundamental operation categorized under Data Manipulation Language (DML). Using the `INSERT INTO` statement, developers add new rows of data into specified columns of a table. This statement requires specifying the table name and the values to be inserted, ensuring accurate placement of data according to defined column constraints and data types. Mastering `INSERT INTO` enables efficient management of database records, supporting robust data handling and manipulation within SQL environments.
05:27min
Alter Table
In SQL databases such as MySQL, the `ALTER TABLE` statement is a critical component of Data Definition Language (DDL), used to modify the structure of existing database tables. This statement allows database administrators and developers to add new columns (`ADD`), modify existing columns (`ALTER COLUMN`), drop columns (`DROP COLUMN`), add constraints like primary keys or foreign keys (`ADD CONSTRAINT`), and perform other structural changes to tables. `ALTER TABLE` is essential for evolving database schemas to accommodate changing business requirements or optimizing database performance. Mastering the use of `ALTER TABLE` ensures effective database management, supporting scalability and adaptability in SQL environments.
04:51min
DML Update
In SQL databases such as MySQL, the `ALTER TABLE` statement is a critical component of Data Definition Language (DDL), used to modify the structure of existing database tables. This statement allows database administrators and developers to add new columns (`ADD`), modify existing columns (`ALTER COLUMN`), drop columns (`DROP COLUMN`), add constraints like primary keys or foreign keys (`ADD CONSTRAINT`), and perform other structural changes to tables. `ALTER TABLE` is essential for evolving database schemas to accommodate changing business requirements or optimizing database performance. Mastering the use of `ALTER TABLE` ensures effective database management, supporting scalability and adaptability in SQL environments.
02:43min
Delete
In SQL databases such as MySQL, the `DELETE` statement is a core element of Data Manipulation Language (DML) used to remove data from tables. This statement allows developers and database administrators to delete specific rows from a table based on specified conditions using SQL syntax. The `DELETE` statement is structured as `DELETE FROM table_name WHERE condition`, where `table_name` identifies the table from which rows are to be removed, and `WHERE condition` specifies the criteria for selecting which rows to delete. Mastery of the `DELETE` statement is essential for maintaining data integrity, managing database storage efficiently, and adhering to data retention policies within database-driven applications. It provides robust capabilities for data manipulation and ensures the accuracy and consistency of data across systems.
0:50min
NotNullUnique
In the context of SQL databases, the terms NOT NULL and UNIQUE are constraints that are typically specified when defining columns within a table. These constraints fall under the broader category of "Data Definition Language" (DDL). NOT NULL: This constraint specifies that a column must contain a value and cannot be null (i.e., empty or undefined). When defining a column, NOT NULL ensures that every row in the table must have a value for that column. UNIQUE: This constraint ensures that all values in a column (or a combination of columns) are unique across the table. It prevents duplicate values from being entered into the specified column(s).
04:40min
PrimaryKey_ForeignKey
In SQL databases like MySQL, PRIMARY KEY and FOREIGN KEY constraints fall under the category of Data Definition Language (DDL). These constraints are used to define relationships and enforce data integrity within database tables. PRIMARY KEY: This constraint uniquely identifies each row in a table. A primary key must contain unique values and cannot contain NULL values. It is defined on one or more columns in a table and ensures that each row is uniquely identifiable. FOREIGN KEY: This constraint is used to link two tables together. A foreign key in one table points to a primary key in another table, establishing a relationship between the two tables. This helps maintain referential integrity by ensuring that values in the foreign key column correspond to valid values in the referenced primary key column.
04:48min
Arithmetic Operators
In the context of SQL, arithmetic operators fall under the category of "Expressions and Operators." These operators are used to perform mathematical calculations on data within queries and other SQL statements. Common arithmetic operators in SQL include: - **Addition (`+`)**: Adds two numbers. - **Subtraction (`-`)**: Subtracts one number from another. - **Multiplication (`*`)**: Multiplies two numbers. - **Division (`/`)**: Divides one number by another. - **Modulus (`%`)**: Returns the remainder of a division operation. These operators can be used in SELECT statements, WHERE clauses, and other parts of SQL queries to manipulate numerical data and generate computed results. Understanding how to use arithmetic operators is fundamental for performing calculations and data analysis within SQL databases.
06:17min
And Operator
03:11min
Not Operator
03:21min
OR Operator
In SQL, the `OR` operator is categorized under "Logical Operators," which are used to combine multiple conditions in `WHERE` or `HAVING` clauses to filter data based on complex criteria. The `OR` operator returns rows that satisfy at least one of the specified conditions, allowing for flexible data retrieval. For example, a query using `OR` can select employees from either the Sales or Marketing departments, thus broadening the search criteria. Mastery of logical operators like `OR` is crucial for writing effective SQL queries that accurately filter and manipulate data based on multiple conditions.
03:21min
Not Operator
The `NOT` operator in SQL falls under the "Logical Operators" section. Logical operators are used to manipulate and evaluate Boolean expressions, particularly in `WHERE` and `HAVING` clauses, to filter query results. The `NOT` operator specifically negates a condition, returning rows where the condition is false. For example, `SELECT * FROM employees WHERE NOT department = 'Sales';` retrieves all employees who are not in the Sales department. Utilizing the `NOT` operator effectively allows for precise data filtering by excluding specific conditions, thereby enhancing the accuracy and flexibility of SQL queries.
03:23min
Between Not Null
This operator is categorized under "Comparison Operators." It is used in WHERE and HAVING clauses to filter data within a specified range. The BETWEEN operator selects values that fall within a given range, including the boundary values. For example, SELECT * FROM employees WHERE salary BETWEEN 50000 AND 100000; retrieves employees with salaries within the specified range.
02:01min
Select Statement
The `SELECT` statement in SQL falls under the category of Data Query Language (DQL). It is used to query and retrieve data from one or more tables in a database, allowing users to specify which columns to fetch and apply various filters, sorting, and grouping options to refine the results. For example, a query like `SELECT column1, column2 FROM table_name WHERE condition;` retrieves data from specified columns and filters the rows based on the given condition. Mastery of the `SELECT` statement is essential for data retrieval and analysis, enabling efficient access and manipulation of data to meet specific needs within SQL databases.
03:31min
Distinct
In SQL, the `DISTINCT` keyword is utilized within `SELECT` statements to retrieve unique values from specified columns in a database table. It falls under the category of "Query Modifiers" or "Query Clauses," allowing developers and database administrators to filter out duplicate rows from query results. For instance, `SELECT DISTINCT department FROM employees;` retrieves distinct department names from the `employees` table, ensuring each department appears only once in the result set. Mastery of `DISTINCT` is crucial for data analysis tasks where identifying unique values is essential, aiding in generating accurate reports and performing efficient data queries within SQL databases.
03:48min
Order_Group Having
In SQL, the `ORDER BY`, `GROUP BY`, and `HAVING` clauses are essential components used to refine and manipulate query results. The `ORDER BY` clause sorts the rows of a `SELECT` statement based on specified columns either in ascending (`ASC`) or descending (`DESC`) order. For instance, `SELECT * FROM products ORDER BY price DESC;` arranges product records by price in descending order. The `GROUP BY` clause categorizes rows with identical values into groups, typically used with aggregate functions like `SUM` or `AVG` to compute summaries across these groups. For example, `SELECT department, AVG(salary) FROM employees GROUP BY department;` groups employees by department and calculates the average salary per department. The `HAVING` clause filters groups based on conditions specified after `GROUP BY`, akin to the `WHERE` clause but applied to grouped data. Mastery of these clauses empowers SQL developers to efficiently organize, summarize, and filter data, facilitating comprehensive data analysis and reporting capabilities within SQL databases.
04:51min
Wild Cards
Wildcards in SQL, specifically `%` and `_`, are utilized within the `LIKE` operator, which is categorized under both "Pattern Matching" and "Query Operators." The `LIKE` operator is employed within `SELECT` statements to search for patterns within column values. The `%` wildcard represents zero or more characters, while the `_` wildcard signifies a single character. For example, `SELECT * FROM employees WHERE last_name LIKE 'Sm%';` retrieves all employees whose last names start with "Sm". Understanding how to effectively utilize wildcards with the `LIKE` operator empowers SQL developers to conduct intricate pattern-matching queries, facilitating robust data retrieval and analysis within SQL databases.
04:55min
Limit Clause
In SQL, the `LIMIT` clause is a critical query modifier used to restrict the number of rows returned by a `SELECT` statement. It falls under the category of "Query Modifiers" or "Query Clauses," enabling developers and database administrators to control the size of result sets. The `LIMIT` clause is typically used to improve query performance by fetching only a specified number of rows from a table, starting from the beginning of the result set. For example, `SELECT * FROM products LIMIT 5;` retrieves the first 5 rows from the `products` table. Mastery of the `LIMIT` clause is essential for optimizing SQL queries, managing data retrieval efficiently, and enhancing the responsiveness of database-driven applications when dealing with large datasets.
05:51min
Aggregate Function
Aggregate functions in SQL, such as `SUM`, `AVG`, `MIN`, `MAX`, and `COUNT`, fall under the category of "Aggregate Functions" or "Aggregate Queries." These functions are used to perform calculations on sets of rows and return a single value that summarizes the data. Aggregate functions operate on groups of rows and are often used in conjunction with the `GROUP BY` clause to group the result set by one or more columns. They are commonly used to calculate totals, averages, counts, minimum values, and maximum values across groups of data. For example, `SELECT SUM(sales_amount) FROM sales;` calculates the total sales amount from the `sales` table. Understanding how to use aggregate functions effectively is crucial for performing data analysis and generating summary reports in SQL databases. They provide powerful capabilities for deriving meaningful insights from large datasets, facilitating decision-making processes in various domains such as business intelligence, finance, and research.
03:11min
Aliases
In SQL, aliases serve as temporary names assigned to columns or tables within queries, enhancing readability and flexibility in query construction. Column aliases are used to rename columns in the result set of a `SELECT` statement, making the output more descriptive or concise. For instance, `SELECT employee_id AS id, first_name FROM employees;` assigns the alias `id` to the `employee_id` column. Table aliases, on the other hand, simplify complex queries by providing shorter, more manageable names for tables involved in joins or subqueries. For example, `SELECT e.employee_id, e.first_name FROM employees AS e;` uses `e` as an alias for the `employees` table. Aliases are crucial in improving query clarity and reducing typing effort, facilitating efficient SQL query writing and maintenance across various database tasks and applications.
01:51min
Views
In SQL databases, "views" are virtual tables created from SQL queries and categorized under "Database Objects." Views do not store data themselves but instead dynamically fetch data from underlying tables when queried. They serve as a way to simplify complex queries, encapsulate frequently used logic, and provide an additional layer of security by controlling access to specific columns or rows of data. For instance, a view can be created to summarize sales data by department, allowing users to query the summarized data without needing to understand the details of the underlying tables. Views enhance query flexibility, improve data management, and contribute to maintaining consistency and security across database operations. Understanding how to leverage views effectively is crucial for optimizing database performance and streamlining data access in SQL-based applications and systems.
03:41min
Stored Procedure
In SQL databases, "stored procedures" are categorized as "Database Objects" that encapsulate sets of SQL statements and procedural logic. They are stored in the database and can be invoked by applications or users to perform specific tasks or operations repeatedly. Stored procedures offer advantages such as modularity, allowing complex operations to be encapsulated and reused across applications, which enhances code reusability and maintainability. They also improve performance by reducing network traffic and optimizing query execution, as procedures are precompiled and stored in the database. Stored procedures enhance security by enabling access controls and limiting direct table access, while also facilitating transaction management to ensure data integrity. Mastering stored procedures is crucial for database administrators and developers to efficiently manage and automate database tasks, streamline application development, and enforce security policies within SQL-based systems.
02:25min
Joins
In SQL, "joins" are fundamental operations categorized under "Table Joins" or "Join Operations." Joins enable developers to combine data from two or more tables based on related columns, facilitating comprehensive data retrieval and analysis. Using joins, SQL queries can fetch data that spans multiple tables, allowing for complex relationships to be navigated and analyzed within a single query. For instance, an `INNER JOIN` retrieves records where there are matching values in both tables, while a `LEFT JOIN` retrieves all records from the left table and matching records from the right table. Joins are essential for integrating data across database tables, enabling efficient data querying and reporting in SQL-based applications and systems. Mastering join techniques is crucial for optimizing database performance and ensuring accurate data retrieval in diverse business and analytical scenarios.
05:49min
Import and Export
In database management, "import" and "export" operations are fundamental aspects of data manipulation and transfer. Importing involves bringing data from external sources like files or other databases into the database system, enabling updates or initial population of tables with external data. Exporting, on the other hand, entails extracting data from the database system and saving it to external destinations such as files or other databases, essential for tasks like generating reports or creating backups. These operations are crucial for data integration, migration, and maintaining data integrity across systems. Efficient management of import and export processes is vital for ensuring data accuracy, accessibility, and adherence to organizational data management practices and regulations.
02:24min

Requirements

  • MySQl

Description

 

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MySQl
Overview
MySQl: Gain a comprehensive overview of Mysql
Duration 01h 23m
Total Fee 3500.00₹
Mode of learning Online
Difficulty level Beginner
Official Website Go to Our Course
Credential Certificate
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MySQl
Highlights
Discover More
  • Earn a Degree of completion
  • Industry-relevant projects
  • Full lifetime access
  • Write complex SQL queries across multiple tables
  • Model real-world data and generate reports using SQL
  • Create your own database or interact with existing databases
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MySQl
Course Details
Skills you will learn
  • MySQL, Installation, Operations

More about this course
  • This course will help the student to improve the skills in SQL and enhance their career in this field
  • This course provides a thorough understanding of SQL syntax and functionalities, equipping you with the skills needed to manage and analyze data effectively in any database environment
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Curriculum
Course 1: Database Operations
  • MySql - DDL
  • Create Table
  • Insert Data
  • Alter Table
  • DML Update
  • Delete
  • NotNullUnique
  • PrimaryKey_ForeignKey
Course 2: Expressions and Operators
  • Arithmetic Operators
  • And Operator
  • Not Operator
Course 3: Logical Operators
  • OR Operator
  • Not Operator
Course 4: Comparison Operators
  • Between Not Null
Course 5: Queries
  • Select Statement
  • Distinct
  • Order_Group Having
Course 6:Pattern Matching
  • Wild Cards
  • Limit Clause
Course 7: Aggregate Function
  • Aggregate Function
Course 8: Aliases
  • Aliases
Course 9: Database Objects
  • Views
  • Stored Procedure
Course 10: Table Joins
  • Joins
Course 11: Data Manipulation
  • Import and Export
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Entry Requirements
Eligibility Criteria
  • No Database, SQL, or MySQL experience needed! Complete beginners to MySQL are welcome
  • All you need is a working computer for this course; PC, Mac, and Linux users are all welcome

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