Amazon Web Services

The objective of this program is to equip participants with the knowledge and practical skills required to use Amazon Web Services for cloud computing, storage, networking, and analytics. The course focuses on foundational and advanced AWS services, including EC2, S3, Lambda, RDS, and cloud security. Participants will learn how to design, deploy, and manage scalable and secure cloud-based solutions for real-world business and technical scenarios.

Category: Analytics

Description

1. Learning Outcomes

Understand the fundamentals of cloud computing and AWS architecture.
Deploy and manage virtual servers using EC2 and containerized applications with ECS/EKS.
Store and retrieve data efficiently using S3, EBS, and RDS.
Implement serverless solutions using AWS Lambda and API Gateway.
Monitor, secure, and optimize AWS resources for cost and performance.
Apply best practices for cloud security, identity management, and compliance.
Use AWS analytics and machine learning services to derive insights from data.

2. Program Highlights & Key Features

Hands-on labs and exercises with core AWS services including compute, storage, and databases.
Training on cloud security, IAM, encryption, and network configurations.
Expert-led sessions on building scalable, high-availability, and fault-tolerant applications.
Case studies across industries such as e-commerce, finance, healthcare, and media.
Exposure to emerging trends like serverless computing, cloud AI/ML services, and DevOps on AWS.

Module 1: Introduction to AWS
Module 2: Core AWS Services
Module 3: AWS for Data Storage and Data Handling
Module 4: AWS for Data Analytics (Conceptual)
Module 5: AWS Deployment and Business Use Cases

Introduction to AWS

What is Amazon Web Services
Cloud Computing Basics (IaaS, PaaS, SaaS)
Benefits of Cloud for Data Analytics
AWS Global Infrastructure (Regions, Availability Zones)
AWS Use Cases in Analytics and Business
Conclusion and QnA

Core AWS Services

Compute Services (EC2 – concept)
Storage Services (S3 – concept and use cases)
Database Services (RDS – basic understanding)
IAM Basics (Users, Roles, Permissions)
Pricing Basics and Cost Awareness
Conclusion and QnA

AWS for Data Storage and Data Handling

Storing Data in Amazon S3
Structured vs Unstructured Data on AWS
Data Upload, Access, and Management
Data Security and Access Control
Use of AWS for Large Datasets
Conclusion and QnA

AWS for Data Analytics (Conceptual)

Role of AWS in Data Analytics
Overview of AWS Analytics Services
Using AWS with Python, SQL, and BI Tools
Data Processing and Analysis Workflow
Analytics Use Cases on AWS
Conclusion and QnA

AWS Deployment and Business Use Cases

Deploying Data Projects on AWS (Conceptual)
Hosting Dashboards and Applications
Scalability and Performance Benefits
Cost Optimization Basics
Real-Life Business Use Cases
Future Scope of AWS in Data Analytics
Conclusion and QnA

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