Buy a Credential, Not an Education

Buy a Credential, Not an Education | Generated by AI

Home 2026.07

Question: Should I spend 20k RMB on this AI master’s, or focus on my existing profile/projects?

I checked your current public profile direction. Your blog already shows a strong AI/software engineering portfolio: LLM-related notes, FineWeb, AI systems, engineering articles, and career planning material. (Zhiwei Li)

My answer: do not treat this master’s as an education investment. Treat it as an HR/immigration signal purchase.

For you, the decision is very different from a normal engineer.

Your current situation

Your “real degree” is already:

11 years engineering experience
        +
HSBC / DBS enterprise experience
        +
open source/blog reputation
        +
training GPT-2 from scratch
        +
AI infrastructure experiments

This is stronger than many MSc graduates.

A random MSc will not make you much better technically.

The question is:

Does the degree remove doors that are currently closed?

Example:

Canada immigration form
US job application
Singapore/HK company HR filter
big company ATS checkbox

Then yes, it has value.

Compare two paths

Path A: Spend 20k RMB on AI Master’s

Output:

Master in Artificial Intelligence
        |
        + diploma
        + thesis
        + foreign university name
        + possible Spain visa route

Then your CV:

AI Engineer
HSBC
Master in Artificial Intelligence
LLM training projects
GitHub/blog

This is cleaner.

Path B: Don’t do it

Spend the next 6-12 months on:

GPT-2 124M -> 1B model
distributed training
vLLM
agents
papers/blog
open source

Your technical profile improves.

But:

Some recruiters still see:

Education:
Associate degree

and ask:

“Do you have a bachelor/master?”

You have already experienced this.

My estimate of ROI

For you:

Technical ROI

Master:

2/10

because you already know more than the curriculum.

Career filter ROI

Master:

8/10

because your weakness is credential.

Immigration ROI

Potentially:

7/10

but verify the exact degree type.

The critical issue:

Official Master's Degree?
or
Título Propio?

Do not pay before confirming.

If you do it, optimize it

Do NOT choose a generic thesis.

Choose:

Master in Artificial Intelligence

Thesis:
Efficient Large Language Model Training on Consumer GPUs

or:

Building Autonomous Coding Agents with Open Source LLMs

or:

Distributed Fine-tuning of Large Language Models

Then it connects:

degree
 +
blog
 +
GitHub
 +
your actual experiments

My recommendation

I would do it if:

Total cost really ~20k RMB
No exams
Thesis topic can be AI/LLM
Diploma wording is acceptable internationally

Because 20k RMB is cheap compared with the upside.

But I would NOT spend 2-3 years doing a normal master’s.

Your situation:

existing engineering reputation: high

missing:
formal degree credential

So buy the credential efficiently.

A possible strategy:

2026

Finish associate degree
        |
        |
AI Master's thesis
        |
        |
Build LLM projects
        |
        |
Apply:
Singapore
Hong Kong
Canada
EU AI engineer roles

The master’s should be a passport stamp, not your main achievement.

References:

GitHub Education eligibility shows why formal enrollment can also provide some ecosystem benefits, but the main value for you is still credential signaling rather than learning resources. (GitHub Docs)
Zhiwei Li public blog/profile index. (Zhiwei Li)
Career action plan discussing degree completion as a priority due to credential filtering. (Zhiwei Li)

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