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Schedule Interview NowMy name is Enoma U. and I have over 6 years of experience in the tech industry. I specialize in the following technologies: Python, Flask, MySQL, GraphQL, MongoDB, etc.. I hold a degree in . Some of the notable projects I’ve worked on include: Email Scrapper, https://github.com/enels/mdn_courses/tree/main/image-gallery, Basic Loan Calculator, Skrabble Game, Intrusion Detection System, etc.. I am based in Benin City, Nigeria. I've successfully completed 10 projects while developing at Softaims.
I employ a methodical and structured approach to solution development, prioritizing deep domain understanding before execution. I excel at systems analysis, creating precise technical specifications, and ensuring that the final solution perfectly maps to the complex business logic it is meant to serve.
My tenure at Softaims has reinforced the importance of careful planning and risk mitigation. I am skilled at breaking down massive, ambiguous problems into manageable, iterative development tasks, ensuring consistent progress and predictable delivery schedules.
I strive for clarity and simplicity in both my technical outputs and my communication. I believe that the most powerful solutions are often the simplest ones, and I am committed to finding those elegant answers for our clients.
Main technologies
6 years
1 Year
3 Years
4 Years
Potentially possible
Flutterwave
Scraps emails from google search query result page based on the search query and also from linkedin connection of a linkedin account
Displays an image in the main thumbnail whenever it's being clicked in the sub gallery and have the option of displaying it in either dark or light colour
The loan calculator calculates clients loan based on the principal and the loan term in real time as data are being entered.
Mimics the scrabble game using the command line interface with only human and computer players available.
An Intrusion Detection System using Deep Neural Network's Back Propagation. The Dataset was obtained from the Canadian Institute for Cybersecurity 2018 Dataset. The network was trained using a 4 layer DNN. For more accuracy it is encouraged that the network is tested using more recent dataset, maybe 2020. I couldn't use the recent dataset as it was too large for me to download (over 120Gb in size).
in Electrical/Electronics Engineering
2005-01-01-2011-01-01