📊 Data Science & Analytics
Python for Data Science, AI & Development
Build real-world expertise in Python across data science, AI, and modern software development. This hands-on course moves from core Python and idiomatic data manipulation through numerical computing, pandas analytics, cleaning and feature engineering, and effective visualization. You will strengthen statistical intuition, practice end-to-end machine learning with scikit-learn, and step into deep learning with PyTorch, including CNNs, RNNs, and transformers. Beyond modeling, you will learn to work with files, web APIs, and databases; manage environments and dependencies; write tested, production-ready code; and package, version, and deploy services with FastAPI and containers. Each module emphasizes practical workflows, performance-aware techniques, and reproducibility—using notebooks and scripts, real datasets, and best practices such as pipelines, cross-validation, and model monitoring. By the end, you can acquire and prepare data, build and explain models, automate experiments, and ship reliable AI-powered applications.
