Day 05 — Part 2: Mock Interview and Resume Review¶
Most candidates who fail data science interviews are not failing on technical knowledge. They fail because their resume undersells their work, their GitHub looks like a tutorial graveyard, and they cannot explain a simple metric decision without hedging for two minutes.
This session is about closing that gap.
Session Overview
Difficulty: All levels (depends on topic) Preparation: ~3 hours active practice (answering out loud) Prerequisites: All of Week 01 and Week 02 · At least one completed project to discuss
What You Will Be Able to Do¶
- Audit your resume against a real hiring checklist
- Structure a project repo the way interviewers expect to see it
- Answer 20+ technical questions with clear, confident answers
- Work through four realistic case studies using a structured framework
- Run a complete 45-minute mock interview on yourself
Session Map¶
| # | Topic | File | Time |
|---|---|---|---|
| 1 | Resume Checklist | 01-resume-checklist.md |
20 min |
| 2 | Portfolio and GitHub | 02-portfolio-github.md |
20 min |
| 3 | Technical Interview Questions | 03-technical-interview-questions.md |
45 min |
| 4 | Case Study Practice | 04-case-study-practice.md |
40 min |
| 5 | Mock Interview Script | 05-mock-interview-script.md |
45 min |
Tip
Do not read these passively. For each section, close the page and write your answer from memory. The gap between "I understood that" and "I can say that clearly on the spot" is where most candidates get caught.
Success
By the end of this session you will have a resume that survives ATS screening, a GitHub profile worth linking, and the muscle memory to answer technical questions without freezing.
Start with 01-resume-checklist