EDUCATION
MS - Computer Science (Honor Cum Laude Award) 2020 -22
Bahria University, Islamabad
CGPA: 3.63 Division: 1st
MSc - Computer Science 2017-19
Agriculture University, Faisalabad
CGPA: 3.16 Division: 1st
BSc - Computer Science 2015-17
Islamia University, Bahawalpur
Muhammad Faizan Marks: 457/800 Division: 2nd
F.Sc - Pre-Engineering 2013-15
Iqra Degree College, Sadiqabad
Marks: 495/1100 Division: 2nd
Matriculation - Science 2011-13
Contact Iqra Public School, Sadiqabad
House 1305, lane 6, Block C, Marks: 670/1050 Division: 1st
sector 4, Airport Housing EXPERTISE
Society, Rawalpindi, Pakistan
Good understanding of programming languages like Java,
+92 333-6042002 Javascript, Jquery, C++, PHP, Python, Matlab and C#.
Both practical as well as theoretical knowledge of Web
faizy2169@gmail.com Designing and Development.
Both practical as well as theoretical knowledge of Artificial
https://www.linkedin.com/in/m Intelligence.
uhammad-faizan-3a48231b9/ CERTIFICATION
Objective 1. Presidential Initiative Artificial Intelligence Computing
(PIAIC)- Arificial Intelligence 2020 – 22
Aim to work in a challenging work Python Programming and Libraries.
environment where I can utilize my Knowledge of Smartgit and Linux(Ubuntu).
expertise in technical skills towards the Practicals of Deep Learning and Machine Learning Based
development and implementation of the Models using Tensorflow.
Knowledge of Amazon (AWS) Services
new ideas, and contributing to growth of
2. Full Stack Web Development Udemy 2022 – Present
the organization.
Certification
Skills Set Front End Tools (Html5, Css3, Javascript, Bootstrap, React,
Angular.js, Node.js)
HTML, PHP, CSS
EXPERIENCE
Bootstrap
Javascript, Jquery Croem Pvt Limited 31 Oct 2022 – 31 Mar 2023
Worked as an Internee Front-end Developer (ASP.NET
ASP.NET (MVC) MVC Framework) using web technologies: Html, Css,
Angular / React Bootstrap, Javascript, Jquery, Azure Devops, Git
Python PROJECTS
C++
Web Designing for pesticide company.
DBMS/SQL Web based application for F1 Racing.
Build deep learning based models for computer vision and
References Natural Language Processing.
References will be provided on demand. Design and development of Deep Learning (DL) based
models for computer vision using Transfer Learning
approach.
Developed auto encoder model for de-noising the
handwriting digits images.