InternshipKey terms and common mistakes
The words you will hear in Data Science work and the mistakes that most often cost interns approvals.
Key terms
| Term | Meaning |
|---|---|
| Data science | Extracting value from data |
| NumPy | Numerical array library |
| SQL | Database query language |
| Imputation | Filling missing values |
| EDA | Exploratory Data Analysis |
p-value | Evidence against the null hypothesis |
Train/test split | Separate data for evaluation |
| Data storytelling | Explaining insights as a narrative |
Common mistakes to avoid
- Analysing data before cleaning missing values and duplicates.
- Showing charts with no title, units or labelled axes.
- Confusing correlation with cause in conclusions.
- Sharing a notebook that only runs on your own machine because of hard-coded file paths.
Want to go deeper? The free Data Science learning path has short modules, games and a certificate for each module.