JEEJULA NEHAPRIYA
Data Analyst| Machine Learning & Power BI Enthusiast
WARANGAL
Summary
Talented professional ready to bring hardworking mentality to Trainee position. Driven to learn position inside and out to maximize contributions and support business and customer objectives. Outstanding organizational skills and knowledge of Data Analyst.
Overview
1
1
year of professional experience
4
4
Certifications
Work History
Trainee
Coding Wise
08.2025 - 02.2026
- Learned new materials, processes, and programs quickly.
- Attended training courses to build understanding of processes, techniques, and industry.
- Participated in on-the-job training, working closely with supervisors and coworkers and asking appropriate questions.
- Supported departmental tasks to increase understanding of industry processes.
Education
B-Tech - CSE- Data Science
VIGNAN INSTITUTE OF TECHNOLOGY AND SCIENCE
Hyderabad09.2024
Intermediate - Math’s, Physics and Chemistry
SRICHAITANYA JUNIOR COLLEGE
Hyderabad, India03.2020
SSC - Science
Kiddie Koop High School
Warangal04.2018
Skills
Programming : Python,Java
Certification
Data Analytics with Generative AI
Timeline
Trainee
Coding Wise
08.2025 - 02.2026
Data Analytics with Generative AI
08-2025
B-Tech - CSE- Data Science
VIGNAN INSTITUTE OF TECHNOLOGY AND SCIENCE
Intermediate - Math’s, Physics and Chemistry
SRICHAITANYA JUNIOR COLLEGE
SSC - Science
Kiddie Koop High School
STRENGTHS
Detail-Oriented, Excellent Communication, Multitasking Abilities, Analytical and Critical Thinking.
projects
1.LIBRARY MANAGEMENT SYSTEM:
Tools/Skills Used : Python,SQL,Pandas,NumPy,Power BI.
- Developed a Library Management System to manage books, members, and transactions efficiently.
- Used Python and Pandas for data handling and SQL for storing/querying records.
- Created Power BI dashboards to visualize book availability and member activity.
- Implemented issue/return tracking and fine calculation features.
2. PARKINSON'S DISEASE ANALYSIS:
Tools/Skills Used: Python, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn.
- Analyzed patient health datasets to identify patterns associated with Parkinson’s Disease.
- Performed data cleaning, feature selection, and preprocessing.
- Built classification models (Logistic Regression, Random Forest) for disease prediction.
- Visualized trends and correlations using Matplotlib and Seaborn.