DA101C

DA101C: Introduction to Data Analytics is an entry-level course that teaches how to turn data into insights. It covers data collection, cleaning, exploration, basic statistics, visualization, and interpretation. Prerequisites are typically basic math; some sections may introduce introductory Python or SQL, but no heavy programming background is required. Core topics include data types/quality, data wrangling (ETL), descriptive statistics, probability basics, data visualization and storytelling, and data ethics/reproducibility. Common tools: Excel, SQL, Python (pandas) or R, and visualization libraries. Format usually blends lectures with hands-on labs, weekly assignments, quizzes, and a capstone data-analysis project. Learning outcomes: perform an end-to-end basic data analysis, create clear visualizations, and present findings to non-technical audiences. Exact content can vary by institution, so check your specific syllabus for precise topics and tools. If you share your school, I can tailor the summary.

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