Data Exploration

  • Free to audit
  • Paid certificate
  • Course certificate
  • Intermediate
  • 4 weeks
Provider
UC Berkeley
Cost
Free to audit
Certificate
Paid, $130
Level
Intermediate
Duration
4 weeks
Effort
4–8 hrs/week
Format
Self-paced
Language
English
Subjects
Data Science, Python, Business
Source
BerkeleyX
Last verified
14 Sep 2026

Free access to the material ends after the course length; graded work and the certificate are paid.

Data Exploration is a four-week BerkeleyX course taught by Richard Huntsinger and belongs to UC Berkeley's Data, Statistics and Programming for Business Decisions sequence (course code DATA88B.1x). It teaches you to explore, visualise and summarise data in Python to support business decisions, working through real-world case studies drawn from several industries. Topics run from Python basics for data exploration through probability, averages, weighted averages and percentiles, to data analysis for business applications, visualisation with histograms, bar charts and scatter plots, and simulation methods for forecasting outcomes. edX classes it as intermediate and self-paced at four to eight hours a week; no prerequisites are listed on the page.

The audit track is free for as long as the course run is active and excludes graded work and the certificate; a verified certificate costs $130, the lowest price among the BerkeleyX courses listed here. Instruction is in English with English transcripts. Inferential Statistics and Linear Regression continue the sequence.

Advertisement

What you’ll learn

  • Use Python basics to load and explore a dataset
  • Compute probabilities, averages, weighted averages and percentiles
  • Summarise data for business decisions using real case studies
  • Visualise data with histograms, bar charts and scatter plots
  • Run simulations to forecast possible outcomes

Who it’s for

Business-minded learners with a little programming exposure who want to analyse data in Python; the sibling courses on inferential statistics and linear regression continue the sequence.

Source: BerkeleyX (opens in a new tab) · Verified · Report a change

Advertisement
Free to auditOpens edx.org Go to course (opens in a new tab)