• Worked extensively with R and Python to explore, clean, and analyze data, and trained machine learning models to uncover insights. Key topics and tools mastered during the internship include:• Data Wrangling: Collection, inspection, cleaning, preprocessing, manipulation, joining, and merging.• Excel for Data Analysis: Data exploration, cleaning, transformation, and advanced Excel tools (Statistical Analysis ToolPak, Power Query, PowerPivot).• Machine Learning: Supervised learning (regression, classification), unsupervised learning, and model evaluation.• Database Management: Relational and NoSQL databases, SQL for data analytics.• Data Visualization & Storytelling: Creating visualizations and dashboards with Tableau and Power BI to communicate insights effectively.

• Gained hands-on experience in deploying and managing containerized applications using Kubernetes, including setting up and configuring nodes, implementing networking policies, and managing multi-container pods and ReplicaSets.• Acquired practical experience in setting up and configuring Jenkins for CI/CD pipelines, including installing Jenkins and Docker on an EC2 server, setting up a Jenkins pipeline to automate code building, Docker image creation, and deployment, and managing containerized applications through automated processes.• Utilized Ansible to configure Apache web servers and deploy content, and used Terraform to provision and manage AWS resources, including EC2 instances, S3 buckets, and VPCs.

Developed and maintained web application using MERN Stack.Team lead of the capstone project, connevting with the team using slack, Ensured code quality by reviewing and validating code for best practices and standards for the team members. Meeting the deadline of the project and delivering the final project.Using git and github to manage the different version of the project and for the teamwork.