Email:firstname.lastname@example.org, Contact: +1-469-***-****
Linked In: https://www.linkedin.com/in/nikitha-yamsani-136ab1181/ OBJECTIVE
Information Systems student seeking for Fulltime opportunity to Work in a dynamic environment that provides me a wide spectrum of experience and exposure and to enhance my skills. SCHOLASTIC DETAILS
Arlington, Texas THE UNIVERSITY OF TEXAS, ARLINGTON Fall 2018-Present MS in Information Systems, (Expected graduation: Spring 2020) Coursework: Python, Data Science, Data Mining, Business Statistics, Project Management, Data Base Systems, Dataware House, Management in Information Technology, Web and Social Analysis, Design and Analysis of systems. Hyderabad, India JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERISTY 2013-2017 B. TECH in Information Technology
Coursework: Java and Data Structures, DBMS, Linux, Cloud Computing, Data Analysis and Algorithms, Software Engineering, Software Testing, Data Mining, Web Technologies, Mobile Application Development, Operating Systems, Computer Networks, Design Pattern.
Programming Skills: Python, Oracle, SQL, My SQL, Java, C. Analytical Skills: Data Science, Machine Learning, Data Mining, Business Statistics, DBMS, Project Management. Office Tools: MS Excel, MS Office, MS Project.
Operating System: Windows, Linux.
Tools and Technique: Eclipse, SAS, Mongo Db, Tableau, Orange. ACADEMIC PROJECTS
• Improvisation of previous model was made with 70% accuracy. Advanced HealthCare System using IoT Dec 2016- Mar 2017
• To create a User Friendly and easy accessible Health care System using Various sensors and Microprocessors.
• The Health System is deployed in various small electronic devices that monitors and reports the user health constantly. Titanic: Machine Learning from Disaster Mar 2019-April 2019
• Kaggle titanic datasets were used to predict the gender and age group of survived people in titanic tragedy.
• Used Logistic, Knn, Cnn, Decision Tree, Naïve Bayes algorithm and developed the model with accuracy of 84% TMDB Box Office Predictions April 2019- May 2019
• Analyze and perform predictions on box office data set from Kaggle.
• Performed cleaning, Feature extraction, Sentiment analysis, Text Analysis, Model Building and Predictions.
• Predicted using best model with Kaggle Score 7.12.