Understand how machines process, interpret, and generate human language.
Explore the evolution of NLP from word embeddings to the self-attention mechanism powering modern Large Language Models. Build tokenizers, text classifiers, and transformer models using Hugging Face and PyTorch.
Understand tokenization, subword algorithms, and vector space semantics.
Implement self-attention, multi-head attention, and positional encodings.
Fine-tune pre-trained transformer models for text classification and question answering.
3 Modules • 12 Lessons • 3h 11m 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.