I am a passionate Computer Science and Engineering student at Jaypee University of Engineering and Technology, with a keen interest in cloud computing, technical content writing, and research and development in computer vision and deep learning.
| Category | Skills |
|---|---|
| Cloud Computing and DevOps | AWS (CloudFormation, CodeCommit, CodeBuild, CodeDeploy, CodePipeline, AWS Amplify, AWS Cloud9, Amazon ECR), Google Cloud Platform (G-cloud), Infrastructure Automation, Git |
| Project Management and Coordination | Team Coordination, Attention to Detail, Market Analysis |
| Data Analysis and Market Research | Data Analysis, Data Visualization, Excel, Market Research |
| SEO & Analytics | SEO, SEMrush, Uber Suggest, Google Analytics, Ahrefs, Backlink Analysis |
| Technical Writing and Content Management | Content Editing & Improvement, Content Analysis, Content Optimization |
| Additional Skills | Operating Systems, Data Structures, SDLC, Agile Methodologies |
- Conducted SEO analysis with AWS Cloud tools, enhancing visibility.
- Demonstrated expertise in AWS CloudWatch, S3, and SEO best practices.
- Performed in-depth content analysis using tools like SEMrush, Uber Suggest, & Google Analytics to identify areas for enhancement.
- Conducted suggestions from market analysis, Data compilation for clarity & Enhancing data quality.
- Authored comprehensive content modules on DevOps principles, infrastructure automation, and AWS toolkits.
- Designed hands-on labs focusing on CI/CD pipelines, serverless computing, and deployment strategies.
- Developed guides for automated testing, security automation, and configuration management.
- Improved model accuracy by 80%.
- Proficient in AI, deep learning, Google Collab/Kaggle.
- Leveraged cloud-based solutions for AI, integrating services like Amazon Sage Maker and Google Collab for ML projects.
- Completed a major in Computer Science and Engineering.
- Studied subjects such as Computer Systems, Operating Systems, Database, SDLC, Digital Marketing, SEO, AWS, GCP, etc.
- Overview: Automated release pipelines in AWS CodePipeline.
- Key Learning: Understanding release pipeline architecture, troubleshooting, adjusting configurations, manual approvals.
- Technologies: AWS CloudFormation, AWS CodePipeline, AWS CodeBuild, AWS CodeCommit, AWS Cloud9, AWS X-Ray.
- Developed a deep learning model to identify fresh and rotten fruits using CNN and Max pooling, Average pooling, and MobileNetV2 architecture.
- Build an NLP solution with Azure AI-Language
- Build an Azure AI Vision solution
- Create an intelligent document processing solution with Azure AI Document Intelligence
- Cloud Engineering
- Perform Foundational Infrastructure Tasks in Google Cloud