DS 101 Assessment
Pre- and post-tests check how your data thinking, Python reading, ESG metric reasoning and verification skills change
How the assessment works
DS 101 uses the platform assessment model: a pre-test first, then learning and practice, then a post-test. The two tests are parallel but not identical, so they show how your skills changed.
- 1Pre-test
Answer before the course to see where your data thinking and code reading start. The pre-test has no pass mark. - 2Learning
Complete the ten lessons of Module 1 and Module 2. - 3Practice
Complete the Guided Lab, the Data Quality Challenge and the Independent Lab. - 4Post-test
Answer after the course. The pass mark is 80%.
What is assessed
Each test has 12 single-answer questions, two per skill area. The questions check judgment, not memorized syntax or ESG regulatory trivia.
| Skill area | Questions |
|---|---|
| Problem framing and evidence boundary | 2 |
| Dataset, schema and units | 2 |
| pandas and reading code | 2 |
| Data quality | 2 |
| ESG metric calculation | 2 |
| Visualization, claims and AI verification | 2 |
Scoring
Scoring happens on the server. Correct answers and explanations never appear on public pages, in downloadable files or in any response before you submit. After you submit, explanations are shown only for the questions you missed.
Info
You need the cohort code and learner code from your instructor to start. Use your learner code, not your real name.
Start
- Start the pre-test: Before the course
- Start the post-test: After the course
- My Learning: Your progress