Data Analysis and Exploration

Coursera MOOC / Non-credit USD 49
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Data Analysis and Exploration

About this course

Strengthen your core data analysis skills by learning how to summarize, profile, and explore datasets in ways that support real business questions. In this course, you’ll build practical experience used in roles such as data analyst, business analyst, reporting analyst, operations analyst, and marketing analyst. You’ll work with common analysis techniques to examine distributions, summarize categorical and numeric data, compare variables, and support segmentation through filtering and exploratory visuals. This is a non-traditional, skill-based learning experience organized around real workplace tasks instead of a fixed lecture sequence. It’s designed to reflect responsibilities you may see in job descriptions, from profiling datasets and building summary tables to exploring variable relationships and helping stakeholders investigate data by segment. You can personalize your path based on what you already know, focus on the skills you need most, and skip content when it’s not necessary. The course curates high-quality lessons from expert instructors, selecting the strongest content for each skill so you can build practical, career-relevant data analysis experience. By the end, you’ll be able to use aggregation, cross-tabulation, frequency analysis, and measures of central tendency and dispersion to summarize data, apply charts and graphical methods to understand distributions and relationships, and use filtering and correlation techniques to support segmentation and exploratory analysis. This course is a strong fit if you already have basic experience with spreadsheets, data analysis, or working with tables and charts.

What you'll learn

  • summarize data using aggregation and cross-tabulation
  • apply graphical methods to understand data distributions
  • conduct frequency analysis and measures of central tendency
  • filter and analyze data for segmentation and exploratory analysis

Course objectives

  • to build practical data analysis skills used in a variety of analytical roles
  • to facilitate personalized learning based on individual experience
  • to provide real-world tasks that align with job descriptions in the analytics field

Skills you'll gain

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