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@goitomy12
Drapeau de Ethiopia Mekelle, Ethiopia
Membre depuis le 27 juin 2018
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goitomy12

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Greetings, I am an Electrical Engineer with MSc. in Microelectronics Engineering and 7 years of experience in higher education, university. My field of expertise include: => Circuit Design, Analog and Digital Electronics, Mixed Signal Processing => Digital Logic and System Design, VLSI. => FPGA & Micro-controllers: 8051, PIC, Arduino, PI, ARM => WSN, DSP, Image Processing, Face & Licence Plate Recognition. => Power Electronics, Power Systems, => Control Systems: System Identification, PID, Fuzzy and IOTs => Algorithms, LABVIEW, Machine Learning and PCB Design. CAD Softwares: => Matlab/Simulink, uKEIL. => Vivado, Quartus, Modelsim, and ActiveHDL => Altium, Eagle, Proteus => ADS, ETAPs, PowerFactory, PSCAD, PLECS, & Power World. Languages: => Matlab, Embedded C/C++, Assembly, Verilog / VHDL and Python. Translation Amharic, Tigrinya to English, German and Spanish. Contact me for any kind of job related to Electrical Engineering. IT IS MY PLEASURE TO HELP YOU.
$18 USD/hr
9 commentaires
4.1
  • 89%Travaux complétés
  • 53%Selon le budget
  • 100%Dans les temps
  • 9%Taux de Réembauche

Portfolio

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Expérience

Lecturer

Sep 2011

I am a lecturer in Mekelle Institute of Technology (MIT), Mekelle University, Ethiopia.

Éducation

MSc in Microelectronics Engineering

2010 - 2012 (2 years)

BSc. in Electrical Engineering

2006 - 2010 (4 years)

Qualifications

Machine Learning (2014)

Coursera

This course provides a broad introduction to machine learning, data mining, and statistical pattern recognition. Topics include: (i) Supervised learning (ii) Unsupervised learning The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical-bioinformatics, audio, database mining, and other areas.

Fundamentals of Digital Image and Video Processing (2014)

Coursera

This course covers the fundamentals of image and video processing. It provide a mathematical framework to describe and analyze images and videos as two- and three-dimensional signals in the spatial, spatio-temporal, and frequency domains. The Course covers theoretical and practices; learning fundamental processing tasks including image/video enhancement, recovery, and compression using state-of-the-art techniques and tools.

Certifications

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