Nishitha Karnati
Intern @ Honeywell | CSE-AIML Student at VIT-AP
- Role
- Information Technology Intern at Honeywell Technologies
- Location
- Vijayawada, AP, IN
- LinkedIn followers
- 500 followers
About Nishitha Karnati
I’m a final-year B.Tech student in Computer Science and Engineering with a specialization in AI/ML at VIT-AP. My passion lies in developing real-world applications that blend Artificial Intelligence, Machine Learning, and Full-Stack development to drive meaningful impact and innovation.Over the years, I’ve worked on several hands-on projects that span across machine learning, cloud, and full-stack domains. Some of my key contributions include a US Visa Approval Predictor built using Python, FastAPI, Docker, MongoDB, and AWS; FineWineML, a supervised ML model achieving 92% accuracy in predicting wine quality; and a MERN-based E-Commerce Platform with integrated payment gateways (Stripe, RazorPay) and JWT-based authentication, deployed on Vercel.I’m skilled in programming languages like Python, Java, JavaScript, and SQL, with practical experience in tools and frameworks such as TensorFlow, Scikit-learn, FastAPI, Flask, React.js, Node.js, MongoDB, Docker, Jenkins, and GitHub Actions. My core interests lie in MLOps, NLP, Deep Learning, CI/CD, and Prompt Engineering.I hold multiple certifications including: AWS Certified Cloud Practitioner (2025),Microsoft Certified: Azure AI Fundamentals (2024),Oracle Cloud Infrastructure 2025 Certified Generative AI ProfessionalMy achievements include being selected among the Top 500 students globally for the Ericsson Edge Academia Program, and among the Top 50 female coders in HackOn with Amazon (Season 5). I’m currently seeking part-time remote opportunities in SDE or Machine Learning roles where I can apply my skills, contribute to impactful solutions, and continue learning and growing in the ever-evolving AI/ML landscape.
Experience
Information Technology Intern
Jan 2026 — Present · Bengaluru, IN
Education
VIT AP UNIVERSITY
CSE, Aritifical intelligence and Machine Learning
2022 — 2026
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