3 – Data Literacy for the Modern Workforce (P:1 C:3)

What Will You Learn?

• Data Hygiene Literacy: Identifying the "5 Sins of Bad Data" (Duplicates, Inconsistencies, Missing Values, Formatting Errors, and Outdated Info) and how to fix them manually or with AI help.
• The "AI-Ready" Standard: Learning the specific criteria that make a dataset usable for machine learning or large language models (LLMs).
• Taxonomy and Metadata: Understanding how to label and categorize files so that AI "retrieval" systems (like a company's internal AI search) can actually find the right information.
• Data Ethics for Everyone: Recognizing the "Human in the Loop" responsibility—ensuring AI output is checked for bias or data leakage before it’s used in business decisions.
• Prompting for Data Transformation: Using AI tools as "interns" to help reformat, summarize, or clean messy data sets safely.