Data Analysis
Turn data into reliable, useful conclusions: clean data, analyse it with spreadsheets, SQL and Python, visualise it honestly and communicate findings with clear limitations.
- Planned 30 days
- About 2 h per day
- 7 planned modules
This course is in development and not yet available for purchase. The planned curriculum below is a draft and may change before launch.
Overview
A practical program on the full analytical workflow. You learn to frame analytical questions, evaluate sources, clean data, use spreadsheets, descriptive statistics, SQL and Python, explore data, handle missing values and outliers, distinguish correlation from causation, reason about sampling and uncertainty, design dashboards, define KPIs, and report to stakeholders reproducibly and responsibly. The capstone is an evidence-based report on a permitted dataset.
What you will be able to do
- Frame analytical questions and evaluate data sources
- Clean and explore data in spreadsheets, SQL and Python
- Apply descriptive statistics and reason about uncertainty
- Choose honest, effective visualisations and dashboards
- Communicate findings and limitations to stakeholders
- Build a reproducible analysis workflow
Before you start
- Basic spreadsheet use
- Secondary-school mathematics
Planned curriculum
A draft outline of the modules being written. Lessons are not available yet, and the outline may change after expert review.
Availability
This course is not on sale yet. It becomes available only after its lessons, assessments and resources pass Yumeora's review. When published, it is planned to be included in Yumeora All-Access.