Data Science with CoPilot and AI Agents: Practical Analysis and Modeling

Modern data analysis is changing rapidly, and AI assistants are now essential tools for writing code, exploring datasets, and building predictive models. This text-based course guides you through using CoPilot and AI agents to accelerate your data science workflow, transforming raw data into actionable business insights. What you'll learn: - Understand the foundational concepts of AI-assisted data science and prompt engineering for code generation - Wrangle and clean messy datasets using CoPilot to handle missing values and merge sources - Create clear visualizations and dashboards using Python libraries like Matplotlib and Seaborn - Build and validate machine learning models for classification and forecasting - Apply anomaly detection techniques like Z-Score and Isolation Forest to spot unusual data patterns - Design custom AI agent workflows to automate repetitive data analysis tasks You will start with core definitions and simple prompts, gradually progressing to complex data pipelines and model evaluation strategies. This course is designed for beginners with no prior data science or AI experience who want to learn modern, AI-augmented workflows. Start reading today to build your first AI-powered data workflows.