What you learn
- Framing a question before touching the data
- Cleaning, joining, and validating real datasets
- Querying with SQL and analyzing in Python or a spreadsheet
- Communicating findings clearly to non-technical stakeholders
What you will understand
- Descriptive statistics and distributions
- Joins, aggregations, and window functions in SQL
- Bias, sampling, and data quality
- Choosing the right chart for the question
How you will practice
- Clean a real, imperfect dataset and document your decisions
- Answer a business question end to end with SQL and a chart
- Write a short, honest readout of what the data does and does not say
What you will build
- A cohort analysis that explains a change in a key metric
- A dashboard that answers a recurring stakeholder question
The proof you build
Evidence that you can take an open question, work real data responsibly, and deliver a defensible, well-communicated answer.
Your work is observed with your consent, scored for independence and assistance, and turned into proof that carries a confidence level. The career path can reach a high-assurance credential, anchored by a scored capstone.
What is not live yet
The desktop app, consent-based observation, scoring, and credentials are in development. Nothing here implies they are live yet.
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