RAJASHEKAR BANDARU

Professional having vast knowledge in Networking and Software Development targeting similar assignments with an organization of high repute preferably in Australia

A focused and goal-oriented fresher having knowledge of Software Development and Networking Knowledge of Operating Systems (OS) coding techniques, Internet Protocol (IP), interfaces and hardware subsystems, reading schematics & data sheets for components Basic knowledge of python, MYSQL and sql and willing to do work on projects like these Knowledge in the development and implementation of network security program, troubleshooting and debugging procedures Sound understanding of end-to-end Software Development Lifecycle encompassing requirement analysis, programming, coding, preparing, reviewing estimation holding technical discussion, impact analysis, re-factoring, deployment and documentation Examined network performance and ensured its maximum availability & reliability employing oversight with respect to network security for timely situational incident analysis and remediation Completed Academic projects in E-booking Tourist Guide and Domain Sensitive Recommendation Excellent communication and negotiating skills with analytical mind of problem solver

• Passport Number: P527087
• Date of Birth: 08/15/1996
• visa status : 408 Temporary Activity Visa
• Married (wife name: Divya pedditi)

• English
• Telugu

E-booking Tourist Guide, 2016, A project on Android application (Tourist Guide) which was basically designed for the tourist so that they can book their journey online. Domain Sensitive Recommendation, 2017, A project on Domain Sensitive Recommendation which was based on CF Recommendation approach to help cope with the information loaded in the real world. It proposed a novel Domain Sensitive Recommendation (DsRec) algorithm to make the rating prediction by exploring the User-Item Subgroup Analysis. Text analysis to identify sensitive data, 2019, A project on Test Analysis which used Python and NLTK so that sensitive data could be extracted from large amount of undefined or unstructured data.