Data Science Essentials: Data Analysis, Machine Learning, and Dev Tools

Modern data science requires both analytical skills and reliable software engineering practices. This written course introduces key data analysis techniques, foundational machine learning algorithms, and essential developer tools used to build, manage, and share reproducible data projects. You will learn how to clean and analyze data, train baseline predictive models, and manage your development environment efficiently. What you'll learn: Understand core terminology and fundamental concepts in data analysis and machine learning; Explore and summarize datasets using structured data manipulation techniques; Build and evaluate basic predictive models for classification and regression tasks; Navigate file systems and run scripts efficiently using the terminal command line; Track code revisions and manage project history using Git version control; Package data workflows and dependencies into portable environments using Docker. The course begins with clear definitions and foundational concepts before moving into practical code walkthroughs and workflow exercises. It is specifically designed for beginners with no prior coding or data science background. Take the first step toward mastering data analysis and modern developer tools today.