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MSc Data science at VIT University | BSc Computer science at VIT University
I completed my BSc in Computer Science undergraduate at VIT University and an MSc in Data Science at VIT University. I am a highly analytical individual with strong communication and programming skills in handling Python packages. I have a solid background in data science, and my understanding of ML and DL models will be utilized. I also have hands-on experience in training machine learning and deep learning models. I worked with the following Python packages to handle models. Pandas NumPy SciPy Matplotlib Seaborn Scikit-Learn Keras TensorFlow PyTorch OpenCV Tools I worked with: Microsoft Excel (pivot tables, pivot charts, statistical analysis) Power BI Tabulae SQL (MySQL, Oracle)
Vellore Institute of Technology
Msc Data science
January 1, 2021 – January 1, 2023
Vellore Institute of Technology
Bsc computer science
January 1, 2018 – January 1, 2021
Prediction of Stroke Diseases using Deep Learning
January 1, 2023 – Present
Design and develop a scalable end-to-end deep learning pipeline using Jupyter Notebook. And also, we can make predictions using the CNN algorithm and save all the data to the MySQL database, which will help with future retraining.
Prediction of Diabetes using ML algorithms
August 1, 2022 – September 1, 2022
Analyzing the datasets of diabetes patients using the machine learning algorithm (Random forest) and giving them an accuracy of more than 90 percent.
Data Visualization on Superstore
March 1, 2022 – April 1, 2022
Analyzing the datasets of US supermarkets, visualizing them through pivot tables in Microsoft Excel, and predicting reports through machine learning algorithms.
Introduction to Data Analytics
Simplilearn
June 25, 2026 – Present
Business Analytics with Excel Beginner Course
Simplilearn
June 25, 2026 – Present
Data Science with Python
Simplilearn
June 25, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate an interest in applying ML/DL to real-world problems (diabetes, stroke prediction). The academic background from a reputable institution (Vellore Institute of Technology) suggests a structured learning approach. The personal projects indicate self-motivation and an ability to work independently. However, the lack of team-based projects or professional experience limits the assessment of collaborative cultural fit.
Soft Skills & Operational Fit
The provided data does not include information to assess soft skills or operational fit. Psychometric test scores are 0, indicating no completed assessment.