Data Foundations
Independently obtain, inspect, and organize data.
- Excel or Sheets
- SQL queries
- Python and Pandas
Learning direction
Data Analytics
Start with problem framing, data cleaning, and statistical judgment to produce explainable, reproducible analysis.
Skill map
From foundations to real delivery
Analytical Thinking
Turn a domain question into a testable analysis question.
- Descriptive statistics
- Sampling, bias, and correlation
- Metric definition
Communication and Validation
Make charts and conclusions withstand scrutiny.
- Data visualization
- Reproducible notebooks
- Boundaries and counterexamples
Real Question
Complete an analysis useful to a campus group or public-data audience.
- Stakeholder interviews
- Analysis report
- Publishing and retrospective
Put the skills to work
Recommended learning and practice items
View all in this direction →CompetitionData · AI · BackendIntermediateDue Oct 1, 2026
IBM Z Datathon 2026
A free global 24-hour student datathon using IBM Z and LinuxONE for real-time AI, privacy-preserving AI, open innovation, and AI-for-good prototypes.
IBM ZFreeGlobal
InternshipBackend · AI · DataAdvancedReady to startDue Nov 1, 2026
Max Planck Computer Science Internship 2027
A worldwide computer-science research internship for bachelor’s, master’s, and doctoral students, with projects matched across AI, data, systems, and software research.
Max Planck Computer ScienceGermanyOn-site
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