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Hi, I’m Azeem Shaiq, a software engineer and AI enthusiast completed Bachelor in Software Engineering at UMT. I enjoy turning ideas into working ML-powered solutions, with a focus on NLP, computer vision, and general Deep Learning workflows. I love learning new tools like Python, PyTorch, and TensorFlow to tackle real-world problems and rapidly iterate on innovative ideas. Beyond my studies, I mentor peers as a tutor at UMT for Programming Fundamentals (Theory + Lab), and I share experiments and tutorials through my YouTube channel Neuro Code, where I livestream coding sessions and explain concepts in approachable language. I’m excited to collaborate on projects that blend software development with AI research and practical impact.…Hi, I’m Azeem Shaiq, a software engineer and AI enthusiast completed Bachelor in Software Engineering at UMT. I enjoy turning ideas into working ML-powered solutions, with a focus on NLP, computer vision, and general Deep Learning workflows. I love learning new tools like Python, PyTorch, and TensorFlow to tackle real-world problems and rapidly iterate on innovative ideas. Beyond my studies, I mentor peers as a tutor at UMT for Programming Fundamentals (Theory + Lab), and I share experiments and tutorials through my YouTube channel Neuro Code, where I livestream coding sessions and explain concepts in approachable language. I’m excited to collaborate on projects that blend software development with AI research and practical impact.

M Azeem Shaiq

AI Engineer, Data Scientist, Programmer, +3

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Hi, I’m Azeem Shaiq, a software engineer and AI enthusiast completed Bachelor in Software Engineering at UMT. I enjoy turning ideas into working ML-powered solutions, with a focus on NLP, computer vision, and general Deep Learning workflows. I love learning new tools like Python, PyTorch, and TensorFlow to tackle real-world problems and rapidly iterate on innovative ideas. Beyond my studies, I mentor peers as a tutor at UMT for Programming Fundamentals (Theory + Lab), and I share experiments and tutorials through my YouTube channel Neuro Code, where I livestream coding sessions and explain concepts in approachable language. I’m excited to collaborate on projects that blend software development with AI research and practical impact.…Hi, I’m Azeem Shaiq, a software engineer and AI enthusiast completed Bachelor in Software Engineering at UMT. I enjoy turning ideas into working ML-powered solutions, with a focus on NLP, computer vision, and general Deep Learning workflows. I love learning new tools like Python, PyTorch, and TensorFlow to tackle real-world problems and rapidly iterate on innovative ideas. Beyond my studies, I mentor peers as a tutor at UMT for Programming Fundamentals (Theory + Lab), and I share experiments and tutorials through my YouTube channel Neuro Code, where I livestream coding sessions and explain concepts in approachable language. I’m excited to collaborate on projects that blend software development with AI research and practical impact.

Available to hire

Hi, I’m Azeem Shaiq, a software engineer and AI enthusiast completed Bachelor in Software Engineering at UMT. I enjoy turning ideas into working ML-powered solutions, with a focus on NLP, computer vision, and general Deep Learning workflows. I love learning new tools like Python, PyTorch, and TensorFlow to tackle real-world problems and rapidly iterate on innovative ideas.

Beyond my studies, I mentor peers as a tutor at UMT for Programming Fundamentals (Theory + Lab), and I share experiments and tutorials through my YouTube channel Neuro Code, where I livestream coding sessions and explain concepts in approachable language. I’m excited to collaborate on projects that blend software development with AI research and practical impact.

Skills

Experience Level

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Peer Tutor at University of Management and Technology (UMT)

January 1, 2023 - Present

Tutored students in Programming Fundamentals (Theory + Lab); mentored juniors, supporting learning across batches (2023–2024) and helping prepared 2000+ students through sessions and hands-on guidance.