Build neural networks that can see, classify, and detect visual patterns.
A comprehensive deep-dive into tensor computations, backpropagation, and state-of-the-art vision architectures. This course covers everything from multi-layer perceptrons to Convolutional Neural Networks (CNNs), transfer learning, and object detection systems.
Construct custom neural network architectures using PyTorch tensors and autograd.
Implement Convolutional Neural Networks for image classification and semantic segmentation.
Fine-tune pre-trained vision backbones with transfer learning techniques.
3 Modules • 12 Lessons • 2h 9m total
Hi, I’m Sharoon, an AI Engineer and your instructor for this course. Over the past 3 years, I have worked at the intersection of machine learning, data science, and software engineering, building intelligent systems that solve real-world problems. My day-to-day work involves moving AI from abstract code into practical applications, and I bring that exact hands-on industry experience directly into the classroom.My teaching philosophy is simple: learn by building. I believe that the best way to master artificial intelligence is not just by studying theory, but by rolling up your sleeves and coding actual models. I break down complex algorithms into simple, practical steps, ensuring you understand both the why behind the math and the how of the deployment. My goal is to transform you from a tech enthusiast into a confident, job-ready builder.