This beginner-to-intermediate Specialization takes you from Python setup and numerical computing to building, tuning, and explaining machine learning and deep learning models. Across three courses, you’ll master data wrangling with NumPy, visualization with Matplotlib and Seaborn, model evaluation and feature engineering, clustering and classification, and NLP workflows using NLTK. The curriculum is project-based and aligned with industry workflows so you graduate with portfolio-ready artifacts that showcase applied AI skills.
Applied Learning Project
You’ll complete end-to-end, notebook-driven projects that mirror real analytics and AI tasks: explore and clean datasets, engineer features, train and compare classifiers, cluster unlabeled data, and deploy multilayer perceptrons. You’ll also build an NLP pipeline (tokenization, NER, parsing) and present results with clear visuals and documentation—just like you would for stakeholders.
