Salman Haider, Acquia Certified Full Stack Drupal Developer - Designer, a Tech Maestro and Coding Ninja who literally BREATHES CODE, over 10+ years of industry experience, building all sorts of websites and applications ranging from real estate, eCommerce, job portals, incubators, government, etc. alongside consultancy and mentoring/teaching digital skills to freshers and midweight developers. Solving complex problems and coding performance/speed efficient algorithms, doing the impossible, and having a swift turnaround time are among my specialties that make him stand out among his competitors. Currently serving the American University of Sharjah as Web Developer (Drupal). Previously served Pfizer as Lead Drupal Developer. *KEY ACCOLADES* - Winner KP APPS Hackathon Challenge, Conducted by KPITB, Code for Pakistan, and The World Bank (2016) - Awarded with the Digital Freelancers Award (2017-18) - Awarded with the Best Web Developer Award at Connected Pakistan Conference (2017) and won 10+ hackathons and tech competitions across Pakistan at SOFTCOM, SOFTEC, NUTEC, ICUETC, CUTEC, ANS, S&T exhibition, and more *TECHNICAL SKILLSET* Web Development Expertise: HTML/CSS/Bootstrap 5.x, JavaScript (ES6 and beyond), PHP8.x/MYSQL, Drupal CMS (6,7,8,9), Version Control using Git, Drush, Well versed with Drupal site building, custom theme development and module development, WordPress Data Science Expertise: Python, SciPy, SciKit, TensorFlow and PyTorch, and other ML and DL libraries and frameworks. Well-versed with a majority of ML and DL models and algorithms i.e SVM, Random Forest, NaiveBayes, Logistic Regression, Linear Regression Regression, KNN, Decision Tree, RNN, CNN, Bi-LSTM, etc. *TEACHING/MENTORING* Taught and mentored 1000+ students and midweight professionals nationwide on a number of technical and soft skills i.e HTML/CSS/Javascript/PHP, Drupal CMS and even freelancing on how to make money online from renowned freelance portals like Fiverr, UpWork, Peopleperhour, and others. *RESEARCH* Currently pursuing research using Machine Learning, Deep Learning, and other information retrieval and NLP techniques for the detection, identification, and eradication of Fake News on OSN.