1. Programming Languages & Frameworks
- Java☕ : Proficient in object-oriented programming and used extensively in backend development and building complex applications. Started using when took AP CSA.
- Python🐍 : Strong in scripting, data analysis, and machine learning, particularly with libraries like Pandas and scikit-learn.
- SQL (PostgreSQL)🗄️: Experience designing and managing databases, optimizing queries, and ensuring data integrity.
- JavaScript⚡: Proficient in building interactive web applications and working with APIs.
- C/C++➕ : Strong foundation in systems programming and algorithm development.
- React⚛️: Developed interactive, dynamic user interfaces, focusing on state management and component-based design.
- Node.js🌿: Built scalable server-side applications and RESTful APIs, focusing on efficiency and performance.
- Flask & Django⚗️: Expertise in backend development, handling user authentication, and database integration.
- AWS☁️: Used for deploying applications, managing databases, and scaling infrastructure with services like EC2, S3, Lambda, and RDS.
- Git🌿: Version control for collaborating on projects, handling branching, merging, and resolving conflicts.
- Docker🐳: Experience containerizing applications, enabling faster development, testing, and deployment.
- Travis CI🤖: Configured automated pipelines for continuous integration and testing.
- Jenkins🎩 : Set up and managed CI/CD pipelines to streamline development workflows.
- AutoCAD📐: Drafted, edited, and managed technical drawings for engineering and maintenance projects to ensure accuracy and consistency with real-world installations.
- Pandas🐼: Proficient in data manipulation, cleaning, and preparation for machine learning models.
- NumPy🧮: Strong understanding of array operations and mathematical computing for data processing.
- scikit-learn🎯: Experience in building and training models for supervised and unsupervised learning tasks.
- Hugging Face😊: Worked with transformers for natural language processing (NLP) tasks, utilizing pre-trained models like BERT.
- BERT🧠: Leveraged BERT for NLP tasks like text classification and question-answering models.
4. Data Visualization & Analysis Tools
- Matplotlib📊: Used to create clear, informative plots and visualizations for data analysis.
- Plotly📈: Built interactive and real-time data visualizations for exploratory data analysis.
- Leadership: Led the AI Society at USF, managing over 200 members and coordinating workshops, events, and funding.
- Collaboration: Worked closely with cross-functional teams during internships and projects, ensuring smooth integration between frontend and backend teams.
- Problem-Solving: Skilled in tackling complex technical challenges, from building trading bots to enhancing AI models in research.