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SQL

Structured Query Language (SQL)

Unlock the power of data with our in-depth SQL and Relational Databases course! Designed for beginners and aspiring data professionals, this curriculum will take you from foundational concepts to advanced database operations, equipping you with the skills to design, query, and optimize databases across multiple platforms.

Original price was: ₹2,500.00.Current price is: ₹1,199.00.

About This Course

This course covers everything from basic SQL queries to advanced database operations, giving you hands-on experience with MySQL, PostgreSQL, Oracle, and SQLite. Whether you’re a student, aspiring data analyst, or developer, this course will equip you with the essential skills to design, manage, and optimize databases for real-world applications.

What You’ll Learn:

  • SQL Essentials: Understand relational database concepts, master SQL commands, and learn to filter and aggregate data.

  • Database Operations: Perform CRUD operations, join tables, and write complex subqueries.

  • Advanced Techniques: Work with views, indexing, transactions, and error handling.

  • Database-Specific Features: Explore unique capabilities of MySQL, PostgreSQL, Oracle, and SQLite.

  • Python Integration: Use Python to interact with databases, run queries, and build dynamic applications.

  • Optimization & Projects: Learn query optimization techniques and complete a capstone project integrating multiple databases.

By the end of this course, you’ll be confident in handling any SQL challenge, from small apps to large-scale systems. Let’s embark on your SQL journey and build the foundation for a thriving data-driven career!

Course Content

Module 1 - Introduction to Relational Databases and SQL
Fundamentals Of Databases
 
Relational Database Concepts
 
Overview of SQL
 
Installing MYSQL
 
Writing SQL Queries
 
Select, Insert And Update
 
Delete command
 
Operators And Wildcards
 
Aggregation And SQL Clauses

Constraints in SQL
 
Joins in SQL
 
Practice Questions On Joins
 
Subqueries in SQL
 
Practice On Subqueries

Views in SQL
 
Indexes in SQL
 
Practice on Views and Indexes
 
Transactions in SQL
 
Error handling in SQL

Part 1 – MySQL Advance Features
 
Part 2 – MySQL Advance Features
 
Part 1 – Advance Features of PostgreSQL
 
Part 2 – Advance Features of PostgreSQL
 
Oracle Advance Features
Intro to SQLite and Setting up a Simple APP
 
JSON And Optimizing Queries
Setting Up Connection
 
CRUD Operations
 
Python with PostgreSQL
 
Error Handling
 
Python with Sqlite3
Integration With Two Databases
 
MySQL And PostgreSQL
 
MySQL And SQLite
 
PostgreSQL And SQLite
 
Query Execution Plans and Optimizing Queries

MultiDB-Master

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FAQs (Frequently Asked Questions)

Courses are designed from scratch by professionals. No prior knowledge is needed.

The course is usually delivered through a combination of video lectures and projects.

After completing a SQL course, career prospects include roles such as Software Engineer (Backend), Cloud Database Specialist, Business Intelligence Developer, Data Engineer, Data Analyst, SQL Developer, Database Administrator and Business Intelligence Professionals

₹1199/- ₹2500/-
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Total Duration

18.5 Hours

Total Lessons

41

Course Validity

1 year

Level

All Levels

Job Opportunities

Cloud Database Specialist
Business Intelligence Developer
Data Engineer
Data Analyst
SQL Developer
Database Administrator
Software Engineer (Backend)

Target Audience

  • Business Intelligence Professionals
  • System Administrators
  • Data Analysts
  • IT Professionals
  • Students
  • Software Developers
  • Researchers

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    Structured Query Language (SQL)

    Demo Lecture

    Course Curriculum

    Module 1 – Introduction to Relational Databases and SQL

    1: Fundamentals of Databases

    • What are Databases? Types and Applications
    • Relational Database Concepts (Tables, Keys, Relationships)
    • Overview of SQL

    2: Setting Up Databases

    • Installing MySQL

    3: Basic SQL Commands

    • Writing SQL Queries: SELECT, FROM, WHERE
    • Filtering Data: Operators and Wildcards

    4: Aggregation and Grouping

    • Aggregate Functions: COUNT, SUM, AVG, MIN, MAX
    • GROUP BY and HAVING Clauses


    Module 2 – SQL Operations Across Databases

    1: Data Manipulation in SQL

    • INSERT, UPDATE, DELETE Statements
    • Working with Primary and Foreign Keys

    2: Joining Tables and Subqueries

    • Types of Joins: INNER, LEFT, RIGHT, FULL OUTER
    • Writing Subqueries: Inline and Correlated

    3: Data Constraints and Schema Design

    • Defining Constraints: NOT NULL, UNIQUE, CHECK
    • Creating and Altering Tables

    Module 3 – Advanced SQL Concepts

    1: Views and Indexing

    • Creating and Managing Views
    • Indexes for Performance Optimization

    2: Transactions and Error Handling

    • ACID Properties and Transactions
    • COMMIT, ROLLBACK, SAVEPOINT
    • Error Handling in Oracle and PostgreSQL

    Module 4 – Database-Specific Features

    1: MySQL Advanced Features

    • Working with JSON Data
    • Stored Procedures and Triggers

    2: PostgreSQL Advanced Features

    • Working with JSONB and Arrays
    • Using PL/pgSQL for Procedural Programming

    3: Oracle Advanced Features

    • Using PL/SQL for Stored Procedures and Triggers
    • Cursors and Error Handling

    Module 5 – SQLite and Lightweight Databases

    1: Introduction to SQLite

    • What is SQLite? Use Cases and Features
    • Creating and Managing SQLite Databases

    2: SQLite Advanced Operations

    • Working with JSON and Text Data in SQLite
    • Optimizing SQLite Queries

    Module 6 – Python Connectivity with Databases

    1: Python and MySQL

    • Setting Up MySQL Connector for Python
    • Performing CRUD Operations in MySQL Using Python

    2: Python and PostgreSQL

    • Setting Up psycopg2 for PostgreSQL
    • Query Execution and Error Handling in Python

    3: Python and SQLite

    • Using SQLite in Python with sqlite3 Module
    • Building SQLite Databases Dynamically

    Module 7 – Integration Projects and Optimization

    1: Integrating Multiple Databases

    • Connecting Python to Multiple Databases Simultaneously
    • Data Migration Between Databases

    2: Query Optimization Techniques

    • Understanding Query Execution Plans
    • Indexing Strategies Across Databases

    Project

    Cloud Computing With AWS

    Demo Lecture

    Course Curriculum

    Module 1: Introduction to Cloud Computing

    • Overview of Cloud Computing
      • Definition, Characteristics, and Benefits
      • Types of Cloud Services: IaaS, PaaS, SaaS
      • Deployment Models: Public, Private, Hybrid, and Community Clouds
    • History and Evolution of Cloud Computing
      • From On-Premises to the Cloud
      • Major Milestones and Innovations
    • Why AWS for Cloud Computing?
      • AWS Overview and Market Leadership
      • Global Infrastructure: Regions and Availability Zones

    Module 2: Core Concepts of Cloud Computing

    • Virtualization Basics
      • AWS EC2 Instances as an Example of Virtual Machines
      • Amazon ECS and EKS for Container Management
    • Networking in the Cloud
      • Amazon VPC: Subnets, Route Tables, and Gateways
      • Elastic Load Balancing (ELB) and AWS Direct Connect
    • Storage in the Cloud
      • AWS S3 for Object Storage: Buckets, Access Policies, and Lifecycle Management
      • Amazon EBS for Block Storage

    Module 3: Cloud Infrastructure and Architecture

    • Scalability and Elasticity
      • Using AWS Auto Scaling for Elastic Workloads
      • Horizontal and Vertical Scaling with Amazon EC2
    • Cloud-Native Architecture
      • Serverless Computing with AWS Lambda
      • Orchestrating Containers with Amazon ECS and EKS
    • High Availability and Disaster Recovery
      • Multi-Region Deployments with AWS Route 53
      • Backup Strategies Using AWS Backup

    Module 4: Security in the Cloud

    • Cloud Security Fundamentals
      • Shared Responsibility Model with AWS
      • Identity and Access Management (IAM) for User Roles and Permissions
    • Data Security
      • Encryption Using AWS Key Management Service (KMS)
      • Monitoring and Auditing with AWS CloudTrail
    • Compliance and Governance
      • Managing Compliance with AWS Config and Artifact

    Module 5: Cloud Service Models

    • Infrastructure as a Service (IaaS)
      • Provisioning EC2 Instances
      • Managing Storage and Networking with Amazon VPC and Elastic IPs
    • Platform as a Service (PaaS)
      • Deploying Applications Using AWS Elastic Beanstalk
    • Software as a Service (SaaS)
      • Exploring AWS Marketplace for SaaS Solutions

    Module 6: DevOps and Automation in the Cloud

    • Cloud and DevOps Integration
      • Building CI/CD Pipelines with AWS CodePipeline and CodeDeploy
    • Infrastructure as Code (IaC)
      • Automating Resource Provisioning Using AWS CloudFormation and Terraform
    • Monitoring and Logging
      • Application Monitoring with Amazon CloudWatch

    Module 7: Cloud Economics and Optimization

    • Cost Management in AWS
      • Exploring AWS Pricing Models
      • Using AWS Budgets and Cost Explorer to Track and Optimize Costs
    • Resource Optimization
      • Reserved Instances and Savings Plans in EC2
      • Using Trusted Advisor for Recommendations
    • Sustainability in the Cloud
      • AWS’s Commitment to Renewable Energy and Carbon Footprint Reduction

    Module 8: Emerging Trends in Cloud Computing

    • Edge Computing with AWS
      • AWS IoT Greengrass and AWS Wavelength
    • AI and Machine Learning in the Cloud
      • Using Amazon Sage Maker for Machine Learning Workflows
    • Hybrid and Multi-Cloud Strategies
      • Managing Hybrid Environments with AWS Outposts

    Module 9: Projects

     

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