Week 12: Capstone Completion & Career Prep

Ship the project. Walk into the interview. Start your career.

Duration: 7 Days | Level: Final week | Graduation

You have built the skills. You have built the project. This week is about packaging both - so a recruiter who spends six seconds on your resume and three minutes on your portfolio decides to schedule a call. We close out with deployment, documentation, resume, LinkedIn, interview prep, and a final presentation. By Friday, you graduate.

What You'll Do This Week

Day 1

Ship It

Deployment day

Deployment checklist

  • All R scripts re-run from a fresh checkout without manual steps
  • renv pins package versions
  • Secrets read from environment variables, not committed
  • App opens cleanly on a phone-size screen
  • showNotification("Loading...") for slow operations
  • Footer credits you (name, GitHub URL, LinkedIn)

Deploy in five clicks

Open RStudio, open app.R, click the blue Publish icon, pick shinyapps.io, choose files, click Publish. Your app gets a URL like your-name.shinyapps.io/capstone.

Day 2

Documentation and Portfolio

If it's not on GitHub, it doesn't exist. Your repository README is the second most important thing in your portfolio (after the live URL).

The README that lands interviews

  1. Title + one-sentence pitch
  2. Screenshot or animated GIF of the live app
  3. Live demo link
  4. Problem statement
  5. Data sources and licence
  6. Methods (one short paragraph)
  7. Key findings - 3 bullet points
  8. How to run locally (5 commands max)
  9. Folder structure
  10. License + your contact
Day 3

Resume and LinkedIn

The fresher data-analyst resume, in one page

  1. Header: name, role, email, phone, GitHub, LinkedIn, location.
  2. Summary (2 lines): "Data analyst trained at EDUSHARK with hands-on projects in SQL, R Shiny and Power BI. Seeking analyst role in BFSI / Healthcare / Retail."
  3. Skills: SQL, R, Tidyverse, R Shiny, Power BI, Tableau, Excel, Python (basics), Git.
  4. Projects (the heart - 3-4 entries). Each: title → tech → outcome with a number.
  5. Certifications - EDUSHARK + any Coursera / Datacamp.
  6. Education - last; projects matter more.
ATS killers to avoid: tables (many scanners can't read them), icons-as-images, two-column Canva PDFs, photos. Plain one-column ATS-friendly templates from flowcv.com or rxresu.me win.

LinkedIn checklist

  • Professional photo and brand-coloured banner
  • Headline: "Aspiring Data Analyst | SQL, R Shiny, Power BI"
  • About: same pitch as resume summary, two paragraphs
  • Featured: pin the capstone live URL and GitHub
  • Skills + endorsements: add 10 from this course
  • Open to Work badge ON (recruiter-visible)
Day 4

Technical Interviews

The five buckets

SQL live coding

Window functions, CTEs, second-highest salary, sessionisation.

Statistics

Explain p-value, CLT, when to use median.

Case studies

"Revenue dropped 10% - diagnose."

Tool comparison

"Why R Shiny over Power BI here?"

Your project

Walk through the capstone end-to-end.

A practice plan

  • LeetCode SQL - aim for 60 problems across Easy + Medium.
  • Stratascratch / Datalemur for case-style questions.
  • Khan Academy stats refresher.
  • Pair-mock with a peer once a week.
Day 5

Behavioural Interviews

The STAR framework: answer behavioural questions in four beats - Situation, Task, Action, Result. The result must be quantified.

Prepare seven stories

Cover: leadership, conflict, failure, learning quickly, handling ambiguity, persuading without authority, beating a deadline. One strong story per theme is enough; the same story can answer two questions.

The "tell me about yourself" opener

Three minutes, three beats: Where I am now (course, recent projects), how I got here (background + motivation), where I want to go (the role I'm interviewing for).

Questions you should ask

  • What does success look like at six months?
  • Walk me through a recent analysis the team ran end-to-end.
  • What's the team's tooling - SQL, BI, scripting languages?
  • How is data quality maintained?
Day 6

Presentation Practice

Slide outline (7 slides)

  1. Title + your name + role you want
  2. The business question (one sentence)
  3. The data and method (one slide each, max)
  4. Key findings - three slides, one finding each
  5. Live demo of the Shiny app (2-3 minutes)
  6. Recommendations - three actionable bullets
  7. Q&A prep slide (hidden) with anticipated questions

Five delivery tips

  • Open with the punchline, not the methodology.
  • Rehearse the demo on the actual screen-share setup once.
  • One number per slide, big, with context.
  • Pause after questions; do not fill silence.
  • End with a confident, written next-step.
Day 7

Graduation

Final 15-minute live presentation to a panel. Live demo of deployed R Shiny dashboard. Q&A with peers and instructors. Certificate of completion.

Grading

  • Capstone project quality - 40%
  • Presentation and communication - 30%
  • Documentation and portfolio - 20%
  • Program participation - 10%

Congratulations.

You have completed twelve weeks of intensive training in Data Analytics, SQL, R Programming, R Shiny and BI tools. You have a deployed dashboard, a public portfolio, and the habits of an analyst.

Now go and apply.