Mobile Application development both for android and ios using flutter by google...

A. AWS (Public Cloud) :• Setting up the system for AWS• AWS Storage: The S3 Bucket• The Root Module• AWS Compute: • AMI Data, Key Pair, and the File Function• The EC2 Instance• User Data and Template Files• AWS Networking:• VPC, IGW, and Route Tables• Subnets, Security, and the Count Attribute• AWS infrastructure : IAM policies, Auto-scaling,Lambda, Cloud Trail, Cloud Watch, RDS, Cloudfront• AWS : HA Architecture• Setup large-scale, high-traffic, redundant, cloud-based Iaas/PaaS/SaaS environment at a Public Cloud provider like AWS• B. OPENSTACK (Private Cloud with Containers) :• Openstack Overviewo Nova architecture o VM provisioning walkthrough• OpenStack Networking Overviewo KVM networking with Linux bridgeso Single‐host vs multi‐host networkingo The role of Network ManagerFloating IPso Traffic Flow• Openstack Storage Overviewo The Ring, RingBuilder, partitioningo Account, container and object serverso Replicationo Security/ACLso Deployment and Operations• Automated Installation of Openstacko Service Architectureo Openstack cookbooks – Management server, Keystone, Glance, Quantum (Neutron), Nova, Cinder, Horizon• OpenStack Magnumo OpenStack's Container Infrastructure Management Service (Magnum)o Managing Clusters with Magnum Using the CLI and DashBoardC. Terraform (with AWS & OpenStack) :o Infrastructure As Code In AWS / OpenStack With Terraformo  Configuring and Creating AWS / OpenStack Resource with Terraform o Terraform Concepts Terraform Concepts: Resources ,Data Sources,Locals,Outputs,Templates And Files,Providers,Variableso Terraform Modules Terraform Custom Modules and Registry Moduleso Terraform State Terraform State - Managing Terraform Plans and Remote Stateo Multiple Environments & Resource Meta Parameters Terraform Workspaces Resource Meta Parameterso Terraform with OpenStack Block Storage Compute Networking Load Balancer Firewall Object Storage

MACHINE LEARNING AND DEEP LEARNING:• Worked in Redhat Linux [RHEL8 and RHEL7]• Researched in various libraries of Python for Data Science and Machine Learning• Learned TensorFlow code-basics working behind Keras• Graph Visualization using various libraries seaborn, matplotlib….• Linear Regression model with customization• Logistic Regression model • K Nearest Neighbor algorithm • K-Means classifier algorithm• Random Forest classifier algorithm for unsupervised learning• Neural Networks (Deep Learning and Deep fake)• Feature Extraction and Feature engineering• Feed forward neural networks (FNN)• Convolutional neural networks (CNN)• Recurrent Neural networks (RNN)• Generative Adversal Neural Networks (GAN)• Restrict Boltzman Machine (RBM) for business model creation• Long Short-Term Memory (LSTM)• Collaborative Filtering with RBM• Autoencoders & Applications in machine learning• How to compose Models in Keras• Saving and Loading a model with Keras• Computer Vision using NN• Text Data Processing• Image / Video processing with various libraries• Speech analytics - Speech to text / Voice tonality• Transfer Learning• Object Detection with SSD• Neural Networks, Convolutional Neural Networks, R-CNNs , SSDs, YOLO & GANs• Transfer Learning and using pre-trained models (VGG, MobileNet, InceptionV3, ResNet50) on ImageNet and re-create popular CNNs such as AlexNet, LeNet, VGG and U-Net• Facial Recognition with VGGFace• Executing, Annotate, Train and Deploy Custom Mask R-CNN modelsDEVOPS:• DevOps CI/CD pipeline to build and deploy a project• Git, Maven, Jenkins, Docker, Kubernetes• Integration of CI/CD with ML/DL• Deploy ML/DL model over kubernetes

Understanding DevOps:• Designing and implementation of Continuous Integration Continuous Delivery Release Management• Architecture, Design, and Implementation of highly scalable and highly available solutions• Monitor infrastructure, set up monitoring tools, review a regular basis and collect stats• Monitoring, troubleshooting and diagnosing infrastructure systems.• Infrastructure usage and monitor• Organize log, event, and monitoring data/ stats and create reports for management• Zero Downtime Deployment Light Dark Green Blue architecture• Execute Unit Tests in CI/CD server Jenkins• Incremental code testing and deployment• Agile Project Tracking tools DevOps Tools in areas like CI/CD Environment Automation, Release Automation, virtualisation, infra as a code or metrics tracking.• Docker & Kubernetes• ELK Stack - (Elastic Search, Logstash, Kibana)• Source Control Management (Git, GitHub & Gitlab)• Jenkins: Multi-staged CI / CD with tools• Introduction to Openshift (PAAS Cloud) with Docker/Podman and Jenkins pipeline• Performance Monitoring Tools (Kibana, Grafana, Prometheus etc)C. Python Scripting Language• Test execution and Reporting with Pytest framework• Implement unit tests in python using the discipline of Test Driven Development(TDD)

I got training in redhat linux 8 operating system from linux World CEO and founder.I can work efficiently on linux operating system with networking and pakage management.