Priyanshi Patel
Data Scientist and Analyst
About me
Final-year B.Sc. IT student with a strong interest in Data Science and Data Analytics. Skilled in Python, SQL, Pandas, Power BI, and data visualization. Passionate about transforming raw data into meaningful insights and creating interactive dashboards to support business decisions. Quick learner with problem-solving abilities, analytical thinking, and enthusiasm for working on real-world data projects. Seeking an opportunity to start my career as a Data Analyst or Data Scientist and grow in a data-driven environment.
Photos
Skills
Work Experience
Administrative Executive
Parul University
March 1, 2025
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November 3, 2025
Managed daily administrative operations and academic coordination. Maintained student records, reports, and official documentation. Coordinated admissions, registrations, and examination processes. Assisted in organizing seminars, workshops, and conferences. Handled departmental communication and correspondence. Supported faculty and PhD scholars in research-related activities. Scheduled meetings, evaluations, and viva voce examinations. Managed filing systems, databases, and confidential records.
Education
Bachelor of Science - Information Technology
Bachelors Degree
July 27, 2023
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Present
Bachelor of Science in Information Technology (B.Sc. IT) focused on programming, database management, data analysis, software development, and modern IT technologies. Currently pursuing final year with strong interest in Data Science and Analytics.
Honors & awards
Research Paper - Emotion Detection Using Simple Neural Network and Text Data
Emotion Detection Using Simple Neural Network and Text Data** is a research project focused on identifying human emotions from text using Machine Learning and Neural Networks. The system analyzes written text such as messages, reviews, or social media posts and predicts emotions like happiness, sadness, anger, fear, or surprise. In this research, text preprocessing techniques such as tokenization, stop-word removal, and vectorization are used to prepare the dataset. A simple neural network model is then trained on labeled text data to classify emotions accurately. The project demonstrates how Natural Language Processing (NLP) and Deep Learning can be combined to understand human emotions from textual data. Key technologies used: Python Neural Networks Natural Language Processing (NLP) TensorFlow / Keras Pandas & NumPy This research highlights practical applications of AI in sentiment analysis, chatbots, mental health support systems, and social media analysis.