Amazon Web Services (AWS) Online Course with Placement

Understand cloud basics and AWS architecture

Launch and manage EC2 Linux and Windows servers

Secure systems using IAM policies, MFA, and role-based access

Store and retrieve data using S3, EBS, and Glacier

Set up RDS databases (MySQL, PostgreSQL)

Configure VPC with subnets, route tables, and security groups

Build scalable and fault-tolerant apps with Auto Scaling and ELB

Use CloudWatch, CloudTrail, and AWS CLI for monitoring and logs

Automate tasks using CloudFormation and Lambda

Real-world projects like e-commerce app deployment, static website hosting, and cloud backup solutions

Cloud Support Trainee: 3.5 5 LPA

AWS Associate-level Engineer: 5 8 LPA

Certified + Projects: 6.5 9 LPA

Remote/contract-based: 25K 75K per month based on skill

Start as: Cloud Support / Junior Cloud Engineer

Move to: AWS Solutions Architect / DevOps Engineer

Later grow into: Cloud Security Specialist / Cloud Consultant

Specialize in: Big Data on AWS, Serverless (Lambda), ML on AWS, or Cost Optimization roles

AWS is the top cloud platform used by startups, banks, and MNCs

AWS Online Course includes step-by-step projects-not just slides or lectures

You learn in a real AWS environment, not simulators

Prepares you for certifications + practical work

Easy to learn, yet deep enough to get interviews quickly

AWS Cloud Administrator

AWS Solutions Architect (Associate)

Cloud Support Engineer

DevOps Associate (with some Linux knowledge)

Junior Site Reliability Engineer (SRE)

Deploy apps on EC2, monitor uptime and usage

Create and manage IAM users, groups, and policies

Build secure, scalable networks with VPC and Subnets

Automate deployments and updates with scripting

Keep backups, track logs, and control costs using billing tools

IT & Software Services

E-commerce and Logistics Tech

Healthcare & Pharma (cloud-based health data)

Finance and Banking

Media, Gaming, and OTT Platforms

Telecom and IoT firms

Amazon EC2 (Elastic Compute Cloud): Amazon EC2 provides you with cloud virtual machines called instances. You can select the OS (such as Linux or Windows), memory, storage, and CPU according to the requirement of your application. It's ideal for hosting applications, websites, or custom software where you require full server control. EC2 is flexible and scalableideal for expanding businesses and developers who are creating applications with unique configurations or performance requirements.

AWS Lambda: AWS Lambda allows you to execute your code without running any servers. You create the function, host it, and Lambda executes it when something invokes itsuch as a file upload or user request. Ideal for little, fast things like data processing, messages, or back-end logic. You only pay for your code run time, which is cost-effective and good for event-driven development.

Amazon ECS (Elastic Container Service): Amazon ECS enables you to run and manage Docker containers on AWS. Containers enable you to bundle your application with all its dependencies such that it will run everywhere the same. ECS simplifies scaling and monitoring such containerized applications. It's commonly used in microservices architecture, where one component of an application runs in a separate container. ECS efficiently handles load balancing, networking, and resource scheduling.

AWS Batch: AWS Batch is used to execute huge amounts of batch computer jobs. They are background processes such as rendering video, processing data, or simulation. You define the job and resources you require, and AWS Batch will take care of provisioning, queuing, and running the job for you. It scales to requirements and operates very well to process large quantities of data and research workloads where thousands of jobs may run at the same time without explicit human intervention.

AWS Elastic Beanstalk: Elastic Beanstalk simplifies web application deployment. Simply upload your code, and it'll do everything for you such as setting up servers, load balancing, and auto-scaling. It supports languages extensively such as Java, Python, PHP, Node.js, and .NET. It is ideal for developers who don't need to worry about infrastructure and simply want to code. It gets you live in a snap and updating and scaling as simple as pie.

Amazon S3 (Simple Storage Service): Amazon S3 is a very robust and secure data storage service for any type of datadocuments, images, videos, backups, or web site files. It's elastic, so it can scale with your data. It has versioning, permissions, and encryption as well. S3 is widely used for data backup, static website hosting, and cloud-native applications. You only pay for what you use, so it's cost-effective for individuals and organizations.

Amazon RDS (Relational Database Service): Amazon RDS simplifies relational database setup and administration as simple as MySQL, PostgreSQL, SQL Server, and Amazon Aurora. Scaling, updating, and backups are automatically taken care of by it. You can easily configure a high-performance cloud-based database system with a single click or double click. It is suitable for web applications, business applications, and data-intensive platforms that require structured, organized, and relational data storage with high reliability.

AWS Glue: AWS Glue is a data integration solution that assists with gathering, cleansing, and formatting data for machine learning or analytics. It hooks into different sources of data and utilizes in-memory or custom scripts to reshape the data into shapes that are of some use. Glue eliminates cataloging, ETL, and pipeline-building activities that require lots of time. It is really helpful when working with data engineers on big data, cloud-based analytics, or business intelligence.

Amazon SageMaker: Amazon SageMaker is a computer vision service for building, training, and hosting machine learning models in the cloud. It possesses data labeling, algorithm testing, and large ML project management tools. With SageMaker, one can now develop AI applications through pre-built algorithms or custom models. It is strong, scalable, and integrates end-to-end machine learning workflowsideal for students entering the field of data science and AI.

Amazon DynamoDB: Amazon DynamoDB is a highly available and scalable NoSQL database service. It's best for applications that must serve enormous amounts of traffic in real-timesuch as online games, shopping carts, or social media streams. DynamoDB scales automatically with usage and is extremely highly available. With it being serverless, there's no concern about hardware or software management. DynamoDB is best suited for applications that require responsiveness and consistency with little setup overhead.

AWS Certification Online Completion Certificate (with module-wise breakdown)

Hands-on Project Certificate (for projects like app deployment)

AWS Certification Practice Kit

Internship Letter (optional based on tasks)

AWS Certified Solutions Architect Associate: It is a foundation certification. It confirms that you know how to build cloud systems that are secure, scalable (can be scaled up with ease), and cost-friendly. It suggests that you can select the right AWS tools for different kinds of projects.

AWS Certified Developer Associate Training: This certification makes you capable of designing, deploying, and running on AWS. It also makes you familiar with the key features of AWS services like Lambda, DynamoDB, and S3. It is appropriate for software developers who want to develop cloud applications.

AWS Certified SysOps Administrator Associate: This one demonstrates that you have expertise with AWS system installation, usage, and management. It's fit if you wish to be a system administrator or managing AWS servers, backups, security, and performance.

AWS Certified Solutions Architect Professional: This is a professional level associate architect certification. This will make you eligible to design large-scale cloud systems for big organizations. You should have real hands-on experience before trying this one.

AWS Certified DevOps Engineer Professional: This advanced certification makes you eligible to apply DevOps (dev + ops) best practices in AWS. It makes you eligible to automate pipelines (CI/CD) and software deployment and updates with ease.

AWS Certified Advanced Networking Specialty: This certification is for networking experts. It shows that you can design and manage complex network systems in AWS. Its ideal for IT professionals who handle hybrid cloud networks or secure data connections between systems.

AWS Certified Security Specialty: This certificate is for senior network professionals. It indicates you are able to design and orchestrate advanced network infrastructure in AWS. It applies to IT experts who oversee hybrid cloud networks or secure data transmission between systems. This certificate turns you into an AWS security master. It transforms you into an expert in securing applications, systems, and data in AWS. It is greatly beneficial if you are to become a cloud security master.

AWS Certified Database Specialty: It means that you are aware of how to choose, store, and relocate databases in AWS. It covers relational (e.g., MySQL) and non-relational (e.g., DynamoDB) databases. It is beneficial for database administrators and data engineers.

AWS Certified Machine Learning Specialty This is to indicate that you can train, deploy, and develop machine learning models using AWS services like SageMaker. It's for data scientists or machine learning engineers to collaborate with artificial intelligence on the cloud.

AWS Cloud Practitioner Certification Foundational: This is an entry-level certificate. This signifies that you have an idea what AWS is, how it works, and how companies can benefit from it. You don't need to be tech-savvy to pull this one offit's an excellent starting point.

AWS Certified Cloud Practitioner Professional: This is one level above the Cloud Practitioner level for fresh entrants. It shows that you are certified to architect cloud solutions and implement them on AWS. It is best recommended for people who already have cloud skills and experience.

Resume Building: We tailor your resume to cloud roles

Mock Interviews: HR + Technical (real-world scenarios)

LinkedIn + GitHub Optimization

Job Referrals & Internal Drives

Offer Letter Support & Role Mapping

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