Cisco Trainer
DOTRUST Lebanon
مجموع سنوات الخبرة :11 years, 11 أشهر
Lecturer on the following topics: Intro to Cybersecurity, Cybersecurity Essentials,
Introduction to Linux, Linux NDG Essentials, IT Essentials, Robotics, and
Artificial Intelligent.
As a member of the Curriculum Development Department, I was responsible for
developing an artificial intelligence curriculum and conducting training for
instructors. (2021)
• Administration and management of Wireless Network
o Very good experience in Ubiquity Unifi System, Controller Pro
• Backup and Security.
o Check that the system is automatically backed up to Synology NAS Storage
o Kaspersky Security center - Management
• Management of Supplies
• User Support
• Planning and implementing future IT developments and undertaking project work.
• Troubleshoot all technology issues.
• Develop and implement policies and securities for Networks data processing and computer systems operations and development.
• Very good experience in Sophos UTM 9, ASA 5506 X with Firepower and Cisco Call manager BE6000S.
• Implementation of Cisco Layer 2 and Layer 3 Switches
• Implementation of Seagate, Qnap and Lenovo NAS Storage, 2 and 4 Bay
• Exchange implementation and migration
• Windows server 2008, 2012.
Broadcasting
o Implementation and installation of Touch’s BTS (indoor-outdoor), by ZTE equipment.
• SWAP and New Sites
• Detect and fix the Radio frequency troubleshooting, solving VSWR alarm problems.
• New sites Establish - management and alarms reporting and troubleshooting|| MLT System.
• BTS internal & external alarm troubleshooting, Remote Electric tilt Alarm.
o Responsible and team leader for ALFA and TOUCH DWDM’s project
• Implementation of Ericson MHL, SPO1460 and SPO1410.
• Network security: ASA 5550, IPS and McAfee SMG 3400
• Administration and Network Security (Windows)
• CPE Speedtouch - configuration and installation.
• Linksys configurations (8 ports).
• Linksys router configuration.
o BBN Network Design:
• Labeling
• Used Microsoft Visio
The objective of my dissertation is to develop and improve a unified graph-based semi-supervised learning framework for jointly estimating the discriminant latent representation and soft label of data instances.
لقد تم حذف الرابط بسبب انتهاكه لسياسة الموقع. يرجى التواصل مع قسم الدعم لمزيد من المعلومات.