Transform raw datasets into actionable predictive models.
Learn the foundational mathematics, data wrangling pipelines, and core algorithms behind modern machine learning. You will build and evaluate supervised and unsupervised models using NumPy, Pandas, and Scikit-Learn.
Master data exploration, feature engineering, and preprocessing pipelines.
Train, evaluate, and tune regression, classification, and clustering models.
Diagnose overfitting, underfitting, and model bias using cross-validation metrics.
3 Modules • 9 Lessons • 2h 17m 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.