AWS  Cloud  

  • What will you learn
  • Course Topic
  • Audience
  • Description
  • Course Objective

Architecting on AWS covers the fundamentals of building IT infrastructure on AWS. The course is designed to teach solutions architects how to optimize the use of the AWS cloud by understanding AWS services and how these services fit into cloud-based solutions.

 

The course covers System Operations on AWS (Sysops) the specific AWS features and tools related to configuration and deployment, as well as common techniques used throughout the industry for configuring and deploying systems.

EC2 with Load-balancer and Auto-Scaling (40 hrs)

  • Basics of EC2
  • SSH
  • Security Groups
  • Private vs Public IPv4
  • EC2 User Data
  • EC2 Pricing
  • AMIs
  • Custom AMI
  • EC2 Instance Types
  • Network and Security in EC2
  • Elastic Load Balancing
  • Auto Scaling Groups (ASG)
  • EBS (Elastic Block Stores)
  • EC2 Running Modes (cost saving)

 

Docker, Container and Kubernetes (60 hours)

  • A thorough introduction to Docker, containers and why you might want to use Docker
  • Detailed setup instructions for macOS and Windows
  • A deep-dive into the core concepts you need to know: Containers & images
  • Learn how to create custom images, use existing images and how to run containers based on such images
  • Get a detailed overview of the core commands you need when working with Docker
  • Learn how to work with data and how to persist data with volumes
  • Explore container networking - with the outside world and between multiple containers
  • Learn how to work with both single and multi-container projects
  • In-depth deployment instructions: Manual deployment and deployment with managed services like AWS ECS
  • Understand Kubernetes core concepts & architecture
  • Learn how to create Kubernetes resources, deployments, services and how to run your containers with Kubernetes
  • Dive deeply into working with data in Kubernetes projects - with different types of volumes
  • Kubernetes networking and DNS service discovery
  • Learn how to deploy your Kubernetes project (at the example of AWS EKS)
  • Learn how to deployyour EKS cluster using CloudFormation
  • Learn how to scale your Kubernetes cluster
  • Learn how to setup kubectlproperly to access your cluster
  • Learn how EKSworks under the hood and its integrations with AWS
  • Learn how to setup administrationusing the Kubernetes Dashboard
  • Learn how to deploy a statelessapplication on EKS and expose it with a public Elastic Load Balancer
  • Learn how to deploy a statefulapplication on EKS and bind it with EBS volumes
  • Learn how to deploy a statefulapplication (such as Wordpress) with EFS network drives
  • Learn to manage your Kubernetes cluster using the AWS CLI and eksctl CLI

 

AWS Serverless with AWS Lambda, API Gateway, Amazon DynamoDB, Step Functions, SAM, the Serverless Framework, CICD & more(40 hours)

  1. AWS Lambda
  2. API Gateway
  3. Amazon DynamoDB
  4. AWS Step Functions
  5. AWS SAM (Serverless Application Model)
  6. The Serverless Framework
  7. AWS CI/CD Tools (Git, CodeCommit, CodeBuild, CodePipeline)
  8. Serverless Best Practices
  9. Serverless Architecture Patterns

 

AWS machine learning certification preparation with Practise Exams(60 hours)

  • S3data lakes
  • AWS Glueand Glue ETL
  • Kinesis data streams, firehose, and video streams
  • DynamoDB
  • Data Pipelines, AWS Batch, and Step Functions
  • Using scikit_learn
  • Data science basics
  • Athena and Quicksight
  • Elastic MapReduce (EMR)
  • Apache Spark and MLLib
  • Feature engineering (imputation, outliers, binning, transforms, encoding, and normalization)
  • Ground Truth
  • Deep Learningbasics
  • Tuning neural networks and avoiding overfitting
  • Amazon SageMaker, including SageMaker StudioSageMaker Model MonitorSageMaker Autopilot, and SageMaker Debugger.
  • Regularization techniques
  • Evaluating machine learning models (precision, recall, F1, confusion matrix, etc.)
  • High-level ML services: ComprehendTranslatePollyTranscribeLexRekognition, and more
  • Security best practices with machine learning on AWS

 

AWS Certified Data Analytics -Specialty DAS-C01 exam preparation with Practise tests (including new coverage of Glue DataBrew, Elastic Views, Glue Studio, and AWS Lake Formation)-60 hours

  • Streaming massive data with AWS Kinesis
  • Queuing messages with Simple Queue Service (SQS)
  • Wrangling the explosion data from the Internet of Things (IOT)
  • Transitioning from small to big data with the AWS Database Migration Service (DMS)
  • Storing massive data lakes with the Simple Storage Service (S3)
  • Optimizing transactional queries with DynamoDB
  • Tying your big data systems together with AWS Lambda
  • Making unstructured data query-able with AWS Glue, Glue ETL, Glue DataBrew, Glue Studio, and Lake Formation
  • Processing data at unlimited scale with Elastic MapReduce, including Apache Spark, Hive, HBase, Presto, Zeppelin, Splunk, and Flume
  • Applying neural networks at massive scale with Deep Learning, MXNet, and Tensorflow
  • Applying advanced machine learning algorithms at scale with Amazon SageMaker
  • Analyzing streaming data in real-time with Kinesis Analytics
  • Searching and analyzing petabyte-scale data with Amazon Elasticsearch Service
  • Querying S3 data lakes with Amazon Athena
  • Hosting massive-scale data warehouses with Redshift and Redshift Spectrum
  • Integrating smaller data with your big data, using the Relational Database Service (RDS) and Aurora
  • Visualizing your data interactively with Quicksight
  • Keeping your data secure with encryption

 

AWS Certified Database Specialty exam preparation(60 hours)

  • Amazon DynamoDBand DAX
  • Amazon RDSand Aurora
  • Amazon Redshift
  • Amazon ElastiCache
  • Amazon DocumentDB
  • Amazon Neptune
  • Amazon ElasticSearch Service
  • Amazon Timestream
  • Amazon QLDB
  • Amazon DMSand SCT
  • AWS CloudFormation
  • Other services: KMS, CloudWatch, VPC, CloudTrail, Lambda, SMS, Secrets Manager
  • Any Graduates(B.A,B.Com,B.Sc)
  • Engineering Students(B.Tech, B.E, M.Tech)
  • BCA,MCA
  • Any Diploma Holder
  • Any Working Professionals
  • Data Warehouse Administrators
  • Database Administrators
  • Software Tester
  • Project Manager
  • MIS Support
  • Manager
  • MIS Support

Introduction to Cloud

What is the cloud?

What is AWS?

What are AWS's core services?

Why do we use AWS?

How Aws billing works ?

Services Covered

  • EC2
  • VPC common services
  • EBS
  • ELB
  • Auto Scalling
  • Elastic IP
  • Beanstalk
  • S3
  • LightSail
  • EFS
  • IAM
  • Route53
  • RDS
  • Cloudfront
  • SES
  • ACM
  • SNS
  • DynamoDB

This course teaches you how to:

  • Make architectural decisions based on the AWS-recommended architectural principles and best practices.

  • Leverage AWS services to make your infrastructure scalable, reliable, and highly available.

  • Leverage AWS managed services to enable greater flexibility and resiliency in an infrastructure.

  • Make an AWS-based infrastructure more efficient in order to increase performance and reduce costs.

  • Use the Well-Architected Framework to improve architectures with AWS solutions.