AWS Cloud Training & Internship Program – January 2023

AWS Cloud

(Batches Start from 4th & 27th January 2023)

About The Program: With the belief to build a healthy ecosystem as per the Industry Standards REGex Software brings a Industrial Training/Internship Program on “AWS Cloud”. We organize Industrial Training/Internship Program for improving the knowledge and skills of the Students/Professionals, so that they can become expert in the field of AWS Cloud and get their Dream Job in Software Development Field in Big MNCs. REGex Software Services’s AWS Cloud course is a valuable resource for beginners and experts. This course will introduce you to Connecting, Managing, Deploying and Updating Cloud from Basics to Advance. If you want to become AWS Certified Solution Architect, REGex introduce this course for you.

Timing

Offline: 04:00 PM – 06:00 PM //05:00 PM – 07:00 PMOnline: 09:00 PM – 11:00 PM

Location

Physical(Jaipur)or Online(Google Meet)

Duration

45 – 50 Days

Participants

30 per Batch

What People Tell About Us

Best affordable Python + Django program with live classes and doubt solving. You can also access to recordings of the classes. Teachers and mentor are very good. All syllabus covered in given time. With multiple live examples. Best part of training is friendly environment. Don't hesitate to enroll if you've never heard the name of this company before. You will not be disappointed.

Shubham Katkar Ex-Student, Django Batch

Competitive Programming is the best course they have - i am part of both python and C++ course. Cracked several interviews with their course, poll test & assignment are always new and beneficial. Best CP course you will find here, i hope this will be beneficial for you

Yaman Singh Ex-Student, CP Batch

Tushar sir is best in delivery. His approach is mind blowing. I have not found any gap although I am from U.S Lots of Big Data tools I have learnt like Hadoop, Hive, Spark, Sqoop & most amazingly Talend ETL Tools which was the most lovely part of training. every component is told in very simple terms with great practical approach

Josh Well Ex-Student, BigData Batch

I recently joined Python Django(Web Development - Full Stack)Course About Course: - I must say instructor makes every concept simple to understand - No Copy Paste,Every line of code is explained - Even given Assignments to work on - Even given Projects to work on If you looking to learn Python Django I highly recommend to go for this course

Salman Khan Ex-Student, Django Batch

I am from UK & loved the teaching. Competitive Programming was the best experience I had in coding. I can truly say the money I spend is worth it. Go for it guys!!

Jack Ryan Ex-Student, CP Batch

What you will Learn

AWS Foundations and Services
AWS Security & Costs
AWS Cloud Services Overview
Compute Services Design, Implementation & Management
Identity and Access Management (IAM)
Auto Scaling Solutions
Virtual Network Services – DNS
AWS Application Deployment
AWS Database Design & Deployment
Additional AWS Services

Study Material

E-Notes
Assignments per day
Weekly Tests
80+ hours on demand Live Video Lectures
24*7 Mentorship Support
Working on Live Projects

Output

Able to think out of the box
Work on multiple projects and Opportunity to get Internship in REGex or in any other Other company through us
Become ready for AWS Solution Architect Certification
Min Annual Salary of cloud Architect is ₹6.6 LPA

Our Students Placed In

Linux & Python

Linux

Introduction to LINUX Operating System and Basic LINUX commands
Operating System
Basic LINUX Commands
LINUX File System
File Types
File Permissions
File Related Commands
Filters
o Simple Filters
o Advanced Filters

Python

AWS Solution Architect

1. Design Secure Architectures Task Statement

Design secure access to AWS resources

Access controls and management across multiple accounts
AWS Identity and Access Management [IAM], AWS Single Sign-On [AWS SSO]
AWS global infrastructure (for example, Availability Zones, AWS Regions)
AWS security best practices (for example, the principle of least privilege)
The AWS shared responsibility model Skills in:
Applying AWS security best practices to IAM users and root users (for example, multi-factor authentication [MFA])
Designing a flexible authorization model that includes IAM users, groups, roles, and policies
Designing a role-based access control strategy (for example, AWS Security Token Service [AWS STS], role switching, cross-account access)
Designing a security strategy for multiple AWS accounts (for example, AWS Control Tower, service control policies [SCPs])
Determining the appropriate use of resource policies for AWS services
Determining when to federate a directory service with IAM roles Task Statement

Design secure workloads and applications

Application configuration and credentials security
AWS service endpoints
Control ports, protocols, and network traffic on AWS
Secure application access
Security services with appropriate use cases (for example, Amazon Cognito, Amazon GuardDuty, Amazon Macie)
Threat vectors external to AWS (for example, DDoS, SQL injection) Skills in:
Designing VPC architectures with security components (for example, security groups, route tables, network ACLs, NAT gateways)
Determining network segmentation strategies (for example, using public subnets and private subnets)
Integrating AWS services to secure applications (for example, AWS Shield, AWS WAF, AWS SSO, AWS Secrets Manager)
Securing external network connections to and from the AWS Cloud (for example, VPN, AWS Direct Connect)

Determine appropriate data security controls

Data access and governance
Data recovery
Data retention and classification
Encryption and appropriate key management Skills in:
Aligning AWS technologies to meet compliance requirements
Encrypting data at rest (for example, AWS Key Management Service [AWS KMS])
Encrypting data in transit (for example, AWS Certificate Manager [ACM] using TLS)
Implementing access policies for encryption keys
Implementing data backups and replications
Implementing policies for data access, lifecycle, and protection
Rotating encryption keys and renewing certificates

2. Design Resilient Architectures

Design scalable and loosely coupled architectures

API creation and management (for example, Amazon API Gateway, REST API)
AWS managed services with appropriate use cases (for example, AWS Transfer Family, Amazon Simple Queue Service [Amazon SQS], Secrets Manager)
Caching strategies
Design principles for microservices (for example, stateless workloads compared with stateful workloads)
Event-driven architectures
Horizontal scaling and vertical scaling
How to appropriately use edge accelerators (for example, content delivery network [CDN])
How to migrate applications into containers
Load balancing concepts (for example, Application Load Balancer)
Multi-tier architectures
Queuing and messaging concepts (for example, publish/subscribe)
Serverless technologies and patterns (for example, AWS Fargate, AWS Lambda)
Storage types with associated characteristics (for example, object, file, block)
The orchestration of containers (for example, Amazon Elastic Container Service [Amazon ECS], Amazon Elastic Kubernetes Service [Amazon EKS])
When to use read replicas
Workflow orchestration (for example, AWS Step Functions)

Design highly available and/or fault-tolerant architectures

AWS global infrastructure (for example, Availability Zones, AWS Regions, Amazon Route 53)
AWS managed services with appropriate use cases (for example, Amazon Comprehend, Amazon Polly)
Basic networking concepts (for example, route tables)
Disaster recovery (DR) strategies (for example, backup and restore, pilot light, warm standby, active-active failover, recovery point objective [RPO], recovery time objective [RTO])
Distributed design patterns
Failover strategies
Immutable infrastructure
Load balancing concepts (for example, Application Load Balancer)
Proxy concepts (for example, Amazon RDS Proxy)
Service quotas and throttling (for example, how to configure the service quotas for a workload in a standby environment)
Storage options and characteristics (for example, durability, replication)
Workload visibility (for example, AWS X-Ray) Skills in:
Determining automation strategies to ensure infrastructure integrity
Determining the AWS services required to provide a highly available and/or fault-tolerant architecture across AWS Regions or Availability Zones
Identifying metrics based on business requirements to deliver a highly available solution
Implementing designs to mitigate single points of failure
Implementing strategies to ensure the durability and availability of data (for example, backups)
Selecting an appropriate DR strategy to meet business requirements
Using AWS services that improve the reliability of legacy applications and applications not built for the cloud (for example, when application changes are not possible)
Using purpose-built AWS services for workloads

3. Design High-Performing Architectures

Determine high-performing and/or scalable storage solutions

Hybrid storage solutions to meet business requirements
Storage services with appropriate use cases (for example, Amazon S3, Amazon Elastic File System [Amazon EFS], Amazon Elastic Block Store [Amazon EBS])
Storage types with associated characteristics (for example, object, file, block) Skills in:
Determining storage services and configurations that meet performance demands
Determining storage services that can scale to accommodate future needs

Design high-performing and elastic compute solutions

AWS compute services with appropriate use cases (for example, AWS Batch, Amazon EMR, Fargate)
Distributed computing concepts supported by AWS global infrastructure and edge services
Queuing and messaging concepts (for example, publish/subscribe)
Scalability capabilities with appropriate use cases (for example, Amazon EC2 Auto Scaling, AWS Auto Scaling)
Serverless technologies and patterns (for example, Lambda, Fargate)
The orchestration of containers (for example, Amazon ECS, Amazon EKS) Skills in:
Decoupling workloads so that components can scale independently
Identifying metrics and conditions to perform scaling actions
Selecting the appropriate compute options and features (for example, EC2 instance types) to meet business requirements
Selecting the appropriate resource type and size (for example, the amount of Lambda memory) to meet business requirements

Determine high-performing database solutions

AWS global infrastructure (for example, Availability Zones, AWS Regions)
Caching strategies and services (for example, Amazon ElastiCache)
Data access patterns (for example, read-intensive compared with write-intensive)
Database capacity planning (for example, capacity units, instance types, Provisioned IOPS)
Database connections and proxies
Database engines with appropriate use cases (for example, heterogeneous migrations, homogeneous migrations)
Database replication (for example, read replicas)
Database types and services (for example, serverless, relational compared with non-relational, in-memory)

Determine high-performing and/or scalable network architectures

Edge networking services with appropriate use cases (for example, Amazon CloudFront, AWS Global Accelerator)
How to design network architecture (for example, subnet tiers, routing, IP addressing)
Load balancing concepts (for example, Application Load Balancer)
Network connection options (for example, AWS VPN, Direct Connect, AWS PrivateLink)

Determine high-performing data ingestion and transformation solutions

Data analytics and visualization services with appropriate use cases (for example, Amazon Athena, AWS Lake Formation, Amazon QuickSight)
Data ingestion patterns (for example, frequency)
Data transfer services with appropriate use cases (for example, AWS DataSync, AWS Storage Gateway)
Data transformation services with appropriate use cases (for example, AWS Glue)
Secure access to ingestion access points
Sizes and speeds needed to meet business requirements
Streaming data services with appropriate use cases (for example, Amazon Kinesis) Skills in:
Building and securing data lakes
Designing data streaming architectures
Designing data transfer solutions
Implementing visualization strategies
Selecting appropriate compute options for data processing (for example, Amazon EMR)
Selecting appropriate configurations for ingestion
Transforming data between formats (for example, .csv to .parquet)

4. Design Cost-Optimized Architectures

Design cost-optimized storage solutions

Access options (for example, an S3 bucket with Requester Pays object storage)
AWS cost management service features (for example, cost allocation tags, multi-account billing)
AWS cost management tools with appropriate use cases (for example, AWS Cost Explorer, AWS Budgets, AWS Cost and Usage Report)
AWS storage services with appropriate use cases (for example, Amazon FSx, Amazon EFS, Amazon S3, Amazon EBS)
Backup strategies
Block storage options (for example, hard disk drive [HDD] volume types, solid state drive [SSD] volume types)
Data lifecycles
Hybrid storage options (for example, DataSync, Transfer Family, Storage Gateway)
Storage access patterns • Storage tiering (for example, cold tiering for object storage)
Storage types with associated characteristics (for example, object, file, block)

Design cost-optimized compute solutions

AWS cost management service features (for example, cost allocation tags, multi-account billing)
AWS cost management tools with appropriate use cases (for example, Cost Explorer, AWS Budgets, AWS Cost and Usage Report)
AWS global infrastructure (for example, Availability Zones, AWS Regions)
AWS purchasing options (for example, Spot Instances, Reserved Instances, Savings Plans)
Distributed compute strategies (for example, edge processing)
Hybrid compute options (for example, AWS Outposts, AWS Snowball Edge)
Instance types, families, and sizes (for example, memory optimized, compute optimized, virtualization)
Optimization of compute utilization (for example, containers, serverless computing, microservices)
Scaling strategies (for example, auto scaling, hibernation)

Design cost-optimized database solutions

AWS cost management service features (for example, cost allocation tags, multi-account billing)
AWS cost management tools with appropriate use cases (for example, Cost Explorer, AWS Budgets, AWS Cost and Usage Report)
Caching strategies
Data retention policies
Database capacity planning (for example, capacity units)
Database connections and proxies
Database engines with appropriate use cases (for example, heterogeneous migrations, homogeneous migrations)
Database replication (for example, read replicas)
Database types and services (for example, relational compared with non-relational, Aurora, DynamoDB)

Design cost-optimized network architectures

AWS cost management service features (for example, cost allocation tags, multi-account billing)
AWS cost management tools with appropriate use cases (for example, Cost Explorer, AWS Budgets, AWS Cost and Usage Report)
Load balancing concepts (for example, Application Load Balancer)
NAT gateways (for example, NAT instance costs compared with NAT gateway costs)
Network connectivity (for example, private lines, dedicated lines, VPNs)
Network routing, topology, and peering (for example, AWS Transit Gateway, VPC peering)
Network services with appropriate use cases (for example, DNS)

Extra Sessions

Additinal Session on GIT, Linux, Docker, AWS Basics, Jenkins and many more for all students.

Fee Structure

Indian Fee

Price: ₹59999/- (Flat 75% off) => ₹14,999/-

International Fee

Price: $1200 (Flat 75% off) => $300

Fee can be paid in No Cost EMI @2500/month

Cashback Policy

You will get your Unique Referral Code after successful paid registration.
You will get ₹1500 Cashback directly in your account for each paid registration from your Unique Referral Code on 15th February, 2023(After Closing Registrations of this program) .
For Example:- If we received 10 paid registration from your Unique Referral Code then you will receive ₹1500*10 = ₹15,000 on 15th February, 2023.

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