Build an interview-ready ML portfolio in 12 weeks —
designed for physics/engineering grads.

Weekly plan + GitHub reviews + real end-to-end projects.
Ship a portfolio you can defend in interviews.

14‑day money-back guarantee. Try it risk-free.
Weekly “do this next” plan
GitHub + repo review
Spaced repetition system

$200/month • Cancel anytime

Courses don’t turn into job-ready portfolios by default.

Most people learn ML through videos and notebooks.
Then job hunting starts—and they realize:

  • their GitHub looks like tutorials,
  • their projects aren’t end-to-end,
  • they can’t explain choices in interviews,
  • and they don’t know what to do next week.
CompuFlair is a guided execution system:
Projects + Weekly Direction + Feedback, so progress compounds.

What you’ll have in 12 weeks

2 completed, interview-ready ML repositories

Clean structure + clear README + results. You won't just "finish projects", you'll finish projects you can defend.

A GitHub profile that signals real ability

Not “I followed a tutorial”. Real work that shows you can code and solve problems.

Confidence explaining decisions

Data cleaning, baselines, evaluation, error analysis - you'll know why you did what you did.

A weekly execution system

So you don’t stall or drift. Consistent progress every week.

How it works (async + structured)

1 Onboard (Day 1–2)

We clarify your goals and current level. You get your first plan and project track.

2 Weekly execution loop (Weeks 1–12)

Each week you get clear next steps. You submit work. I review your GitHub and tell you exactly what to fix next.

3 Ship + polish (final weeks)

We refine repo quality: narrative, README, evaluation clarity, limitations, and how to talk about it in interviews.

What you get

Portfolio + Projects

  • 27 ready-to-run end-to-end ML projects (easy / intermediate / advanced)
  • Personalized project selection (based on your goals + level)
  • End-to-end workflow: problem framing → data → modeling → evaluation → interpretation
  • Repo structure + README templates so your work is presentable

Guidance + Retention

  • Weekly personalized plan (async)
  • GitHub reviews + specific feedback (what to improve this week)
  • My Engram adaptive learning: active recall + spaced repetition for retention
  • Ongoing direction so you always know the next step

No live sessions. This is for people who want to ship real work with guidance—not attend classes.

Proof: real GitHub improvements

Student (Physics background) — Repo transformation

  • Before: scattered notebooks, unclear objective, weak README
  • After: complete repo with clean structure, clear README, evaluation + results
  • What changed: weekly plan + GitHub feedback + iterative improvements
GitHub repo transformation before and after

“I finally knew what to do each week, and my GitHub stopped looking like tutorials.”

Is this for you?

This is for you if:

  • You have a STEM background (physics/engineering/math) and want DS/ML industry roles
  • You know basic Python (pandas + numpy basics is enough)
  • You can commit ~5–10 hours/week
  • You want structure, feedback, and portfolio quality—not more videos

Not for you if:

  • You want live classes or community-first learning
  • You’re starting from zero programming
  • You don't know college level math

Pricing

$200 / month

12-week Portfolio Sprint (paid monthly)
Cancel anytime


  • Weekly plan + guidance (async)
  • GitHub review + feedback
  • Projects + My Engram retention system
14‑day money-back guarantee: Try the first 14 days. If you don’t feel it’s worth it, email me for a full refund.
Book a 15‑min Fit Call

If it’s a fit, you can start immediately and get your Week 1 plan within 24 hours.

Frequently Asked Questions

Is this a course?

No—this is guided execution: weekly plan + feedback + shipping projects.

Do you have live sessions?

No. Everything is async so you can work on your schedule.

How much time per week?

Usually 5–10 hours/week.

What if I already took courses?

Great—this turns course knowledge into an interview-ready portfolio.

What kind of projects?

End-to-end ML projects on real datasets, focused on clarity, evaluation, and presentation.

Do you guarantee a job?

No. We guarantee a structured process and portfolio quality improvements; hiring depends on many factors.

How does the refund work?

If within the first 14 days you feel it’s not worth it, email me and I’ll refund you.

What happens after I book the fit call?

If it’s a fit, you’ll get a short onboarding form (goals, background, time per week). Within 24 hours you’ll receive your first Week 1 plan and the project track we’ll start with.

Ready to stop guessing and start shipping?

Book a 15-minute fit call. I’ll show you the 12-week path and examples of what “good” looks like.

Book a 15‑min Fit Call

14‑day money-back guarantee