2026 College Entrance Exam Application Guide: How to Choose an AI Major? These 4 Directions Are Safest
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The college entrance exam countdown has begun.
Once scores come out, the most headache-inducing thing isn't the exam — it's filling out the application.
Choose a city? A school? Or a major?
Especially this year, with the AI boom, many parents and students are asking: Should we apply for AI-related majors?
As a senior who switched from a law student to a programmer and is now all-in on AI, I'm going to make this clear today.
The Bottom Line First
AI majors are worth applying for, but it depends on the situation.
Not everyone is suitable, and not every school is reliable.
Below, I'll give you a decision framework.
1. Choose a City: Highest Priority
My view: City > School > Major.
Why?
Because where you go to college, you'll most likely intern, work, and even settle down in that city.
Cities where the AI industry is most developed:
| City | Opportunity Density | Cost of Living |
|---|---|---|
| Beijing | ⭐⭐⭐⭐⭐ | High |
| Shanghai | ⭐⭐⭐⭐⭐ | High |
| Shenzhen | ⭐⭐⭐⭐⭐ | High |
| Hangzhou | ⭐⭐⭐⭐ | Medium-High |
| Chengdu | ⭐⭐⭐⭐ | Medium |
| Wuhan | ⭐⭐⭐ | Medium |
If you can go to a tier-1 city, go to a tier-1 city.
If you really can't, at least go to a provincial capital.
There are more AI internship opportunities, more campus recruitment positions, and completely different access to resources.
2. Choose a School: Avoid These Pitfalls
There's a core principle for choosing a school: If you can get into a 985/211, go for it.
But if you can't, watch out for these categories:
❌ Pitfall 1: "AI" Branded Diploma Mills
Some schools have newly opened "Artificial Intelligence" majors, but:
- No reliable faculty
- No decent labs
- Course systems are haphazardly assembled
This kind of major sounds good but doesn't teach you the real stuff.
How to judge: Check whether this major has an independent department, master's/doctoral programs, and industry-partnered labs.
❌ Pitfall 2: AI Majors That Only Teach You How to Tune Parameters
The AI industry changes too fast.
TensorFlow taught today might be unused next year.
What's truly valuable is: Mathematical foundation + Programming ability + Problem-solving mindset.
If an AI major only teaches you "how to use AI tools" without teaching you "why AI is designed this way," be cautious.
✅ Recommended: Choose "Computer Science + X" Rather Than Pure "AI"
What does this mean?
Computer Science + any industry direction is more stable than just studying "Artificial Intelligence."
For example:
- Computer Science + Medicine = Medical AI
- Computer Science + Finance = FinTech
- Computer Science + Law = Legal Tech
AI is a tool, not a goal.
Master the underlying ability, and you can stand firm in any industry.
3. Choose a Major: 4 Safest Directions
Direction 1: Computer Science and Technology (Most Stable)
Suitable for: Students with sufficient scores who want to play it safe
Why recommend:
- A century-old major with a mature curriculum
- Widest employment scope: internet, finance, healthcare, education
- AI is just a branch of computer science. Master the basics, and AI follows naturally
Salary reference: Fresh graduates 8k–20k CNY, higher in tier-1 cities
Direction 2: Data Science and Big Data Technology (Rising Star)
Suitable for: Students good at math who enjoy analyzing data
Why recommend:
- Data position shortage remains large in 2026
- In the era of large models, data is the core asset
- Wide application range, from e-commerce recommendation to medical diagnosis
Core skills: Python, statistics, machine learning basics, SQL
Salary reference: Fresh graduates 10k–25k CNY
Direction 3: Intelligent Science and Technology (Advanced)
Suitable for: Students with high scores who want to deep-dive into AI
Why recommend:
- More AI-focused than computer science
- Courses cover machine learning, deep learning, natural language processing
- If you pursue a master's or doctorate, the salary ceiling is extremely high
4. Final Word
Choosing a major isn't choosing what's hottest, but choosing what's most stable for you.
In the AI era, foundational skills matter most:
- Mathematical thinking
- Programming ability
- Problem-solving mindset
These abilities will serve you for a lifetime, regardless of how the AI industry evolves.
Don't just chase trends; build foundations.
I'm Coder Wanfeng, with 400,000 followers across all platforms, creator of the open-source python-office library, focused on sharing practical Python and AI tips.
My personal website: https://www.python4office.cn — feel free to visit.
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