Rohith Sethumadhavan, IT-IMS Certified Engineer in Windows

Rohith Sethumadhavan

IT-IMS Certified Engineer in Windows

Networking

Lieu
Inde
Éducation
Master, Master Computer Applications
Expérience
3 years, 1 Mois

Partager Mon CV

Empêcher usager


Expériences professionnelles

Total des années d'expérience :3 years, 1 Mois

IT-IMS Certified Engineer in Windows à Networking
  • Inde
  • avril 2012 à août 2012

• IT-IMS Certified Engineer in Windows, Networking, Linux, Hardware from KGISL, Appnomic, Coimbatore (April 2012 - August 2012)

Chennai, Asst Engineer, .Net developer and Data Extraction à Maa Business Solutions Pvt Ltd
  • Inde
  • mai 2011 à décembre 2011

• Maa Business Solutions Pvt Ltd, Chennai, Asst Engineer, .Net developer and Data Extraction
May 2011- Dec 2011
Certification courses

Programming languages VB.net and project trainer à Software and Integrated Solution Private Limited
  • Inde
  • janvier 2006 à décembre 2007

• Programming languages VB.net and project trainer in VB.net (2006-2007) from Software and Integrated Solution Private Limited (SAFE), Palakkad.
• Programming languages C and C++ (2005-2006) from Software and Integrated Solution Private Limited(SAFE), Palakkad.
Computer System Skills
Programming Languages & Databases Known
• C, C++, HTML, VB.Net
• MS Access, SQL Server
Back Office Tools
• Microsoft Office
Concepts
Operating System, DBMS, Networking, System Analysis And Design
Operating Systems
• Windows (98, 2000, NT, XP, Vista, Win 7)


Academic Projects Done As Part Of 6th semester
Project Details
Title Facial Expression Recognition
Software MAT Lab
Duration 4 Months
Team Size 1
Description
The project work proposes an algorithm for facial expression recognition which can classify the given image into one of the seven facial expression categories (happiness, sadness, fear, surprise, anger, disgust, and neutral) . PCA is used for dimensionality reduction in input data while retaining those characteristics of the data set that contribute most to its variance, by keeping lower-order principal components and ignoring higher-order ones. Such low-order components contain the "most important" aspects of the data. The extracted feature vectors in the reduced space are used to train the supervised Neural Network classifier. This approach results extremely powerful because it does not require the detection of any reference point or node grid. The proposed method is fast and can be used for real-time applications

Éducation

Master, Master Computer Applications
  • à Karpagam arts and science college
  • juin 2010

• Master of Computer Applications (2007-2010) from Karpagam arts and science college, Coimbatore, Bharathiyar University, 74.8%

Baccalauréat, Chemistry
  • à University of Calicut
  • janvier 2005

• Bachelor of Chemistry (2002-2005) from N.S.S college, Ottapalam, University of Calicut, 51% • +2 (2000-2002) from Puliyaparamb higher secondary school, Palakkad, Kerala board, 50%

Etudes secondaires ou équivalent,
  • à Seventh Day Adventist Higher Secondary School
  • mars 2000

• SSLC (2000) from Seventh day Adventist school, Ottapalam, State Board of Kerala, 60%

Specialties & Skills

Extraction
Data Extraction
MICROSOFT OFFICE
MS ACCESS

Langues

Hindi
Expert
Malayala
Expert
Anglais
Expert
Tamil
Moyen

Formation et Diplômes

IBM Mainframe (Certificat)
Date de la formation:
December 2010
Valide jusqu'à:
April 2011
Networking And IT-IMS (Information Technology - Infrastructure Management Services) (Certificat)
Date de la formation:
April 2012
Valide jusqu'à:
August 2012