Data Analytics Fundamentals: Terminology and Python EDA Basics

Navigating the field of data analytics requires understanding the exact terminology and tools used in modern data roles. This course breaks down fundamental industry vocabulary and foundational tools into clear, beginner-friendly written explanations. You will start by mastering core concepts across statistics, data engineering, marketing analytics, visualization, and finance before building practical skills in data exploration. By reading through structured text lessons and code snippets, you will learn how to explore datasets, summarize key metrics, and extract actionable insights using Python. You will gain a strong conceptual grasp of the workflows and analytical techniques that modern data professionals use every day. What you'll learn: - Understand foundational concepts in statistics, data engineering, visualization, marketing, and finance analytics - Read and interpret core data science terminology across both technical and business domains - Explore dataset structures and perform exploratory data analysis using Python - Learn how to build and interpret key data visualizations such as histograms - Apply modern dataframe operations to clean, filter, and inspect raw analytical data - Map common industry job requirements to practical analytical workflows. The course begins with essential definitions, industry glossaries, and foundational concepts before advancing into written guides on Python data manipulation and analytical scenarios. This course is designed for complete beginners and career changers with no prior programming experience required. Start building your data literacy today and gain the confidence to read, understand, and analyze data effectively.