I'm a passionate AI Engineer with a year of hands-on experience in turning complex problems into intelligent, end-to-end solutions. My journey has taken me from foundational concepts to building, deploying, and managing machine learning models in real-world scenarios. I thrive on challenges and am dedicated to leveraging AI to create impactful technology.
- 🔭 I’m currently focused on building scalable AI systems and have worked on various Generative AI projects from concept to deployment.
- 🚀 With one year of industry experience, I have: - End-to-End Project Delivery: Successfully engineered and deployed multiple Gen AI projects, including a RAG-based support chatbot on Render and a high-performance (92% accuracy) sentiment analysis API using Flask and a fine-tuned BERT model. - Advanced Model Implementation: Implemented and fine-tuned a diverse range of models, including Large Language Models (LLMs), Generative Adversarial Networks (GANs), and Transformer-based architectures for NLP and computer vision tasks. - Full-Stack AI Development: Proficient across the AI stack, from data management with SQL and NoSQL databases to model development in PyTorch and TensorFlow, and API deployment using containerization with Docker.
- 👯 I’m looking to collaborate on both open-source AI projects & proprietary projects, especially those involving creative applications of LLMs or Multimodal AI.
- 💬 Ask me about Python, Natural Language Processing, Data Science, Deep Learning, Generative AI, and building end-to-end ML pipelines.
- 📫 You can reach me at: [email protected]
1. Introduction to HTML, CSS, & JavaScript - IBM
2. Introduction to Cloud Computing - IBM
3. Crash Course on Python - Google
4. Introduction to Computer Vision and Image Processing - IBM
5. Introduction to Software Engineering - IBM
6. Java Programming for Beginners - IBM
7. AI Agents and Agentic AI with Python & Generative AI - Vanderbilt University
8. Deep Learning with PyTorch - IBM
9. DevOps, DataOps, MLOps - Duke University
10. Django Application Development with SQL and Databases - IBM
11. How to write a research paper - Danyal Education, Connected Pakistan
12. Introduction to Image Generation - Google
13. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning - DeepLearning.AI
14. Advanced Microsoft Power BI - Edureka
15. Build Better Generative Adversarial Networks (GANs) - Deeplearning.AI
16. Fundamentals of AI Agents using RAG and LangChain - IBM
17. Generative AI Advance Fine-Tuning for LLMs - IBM
18. Generative AI with Large Language Models - DeepLearning.AI, Amazon Web Services
19. Microsoft Azure SQL - Microsoft
20. MongoDB: The Complete Guide to NoSQL Database Development - EDUCBA
21. Neural Networks and Deep Learning - Deeplearning.AI
22. What is Data Science? - IBM
