Engineer Selenium

LAKSHMI TAMMANA

Email ID : adjr0q@r.postjobfree.com Mobile :+91-954*******.

Career Objective:

To Work in an Environment that provides a challenging and rewarding career in Automation Testing ensuring a high level job satisfaction,and to give effective efforts towards attainment of organizational goal with exploring wide scope of knowledge and Intelligence.

Skill Summary:

Knowledge on Manual Testing.

Knowledge on understanding and Analyzing Test Requirements.

Knowledge on various phases of SDLC and STLC.

Ability to create Test Scripts, Test Scenarios, Test cases and collect Test Data.

Good knowledge on Automated Testing using Selenium with java and TestNG and JUnit.

Basic knowledge on build automation tool MAVEN.

Knowledge in integration SIKULI with Selenium Web driver.

Practical Experience in Automating Website using Selenium Web driver.

Passionate self motivated engineer having strong hands on knowledge on Automation Testing and problem solving skills.

Academic Qualifications:

MCA in Aditya Engineering College and Technology, Kakinada with an aggregate percentage of 82%.

Bsc in Aditya Degree College for Women, Kakinada with an aggregate percentage of 79%

Intermediate in Aditya Junior College, Kakinada with an aggregate percentage of 75 %.

SSC in Mohan High School, Kakinada with an aggregate percentage of 75 %. .

Certifications :

Certification on Java Programming and Oops Concept

(https://olympus1.greatlearning.in/course_certificate/WVNKCBJG)

Certification on Front End Development HTML and CSS.

https://olympus1.greatlearning.in/course_certificate/FVDIMAMC)

Achievements:

Won PRATHIBHA AWARD regarding my academic performance in Master of Computer Applications.

Software Skills:

Operating Skills: Windows 10, UNIX.

Language: C, JAVA.

Testing Tools : Selenium, Maven

Frameworks: TestNG, JUnit.

Database : SQL,Oracle

Web Technologies: HTML, CSS and Basics of JavaScript.

Academic Project :

Title: Scalable Content Aware Collaborative Filtering for Location Recommendation

Technologies used: Java, Oops, Sql Database.

Operating system: Windows 10.

Project Description:

Collaborative Filtering is a method of making automatic predictions about the interests of user by collecting preferences from any users for location recommendation.

In this project an implicit feedback based content aware collaborative filtering(ICCF)model is used to present the top-k location recommendation based on mobility data to clear of drawing negative samples and gives the clear information where users have features such as profiles and textual content like category hierarchy and geographical information.

Declaration:

I Hereby Declare that above mention information is correct up to my Knowledge and I bear that responsibility for the correctness of the above mentioned particulars.

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