Computer Engineering at California Polytechnic State University-San Luis Obispo

San Luis Obispo, CA · Public · Bachelor's Degree
87 /100
DegreeOutlook Score (Base Case) — assumes in-state tuition
89
Optimistic
87
Base Case
82
Pessimistic
Earnings $111,560/yr (42% vs median)
AI Risk Very High (71% exposed)
Job Market Very Large (167,700 openings/yr)
ROI 28.7x earnings multiple (10.3x out-of-state)
Ranked #3 of 174 Computer Engineering programs Top 5%

How AI Changes the Outlook

Three scenarios based on how aggressively AI disrupts the career paths available to Computer Engineering graduates.

Optimistic
No Disruption
Base Case
Gradual AI
Pessimistic
Aggressive AI
10-Year Earnings $1,371K $1,273K $915K
Earnings Multiple (In-State) 31.0x 28.7x 20.7x
Earnings Multiple (Out-of-State) 11.1x 10.3x 7.4x
Probability of Field Employment 84% 74% 43%
DegreeOutlook Score 89 87 82

10-Year Earnings Projection

*Year 1 uses actual reported earnings. Scenarios diverge as AI impact compounds over time.

4-Year Tuition, In-State (Sticker)
$44,300
Out-of-state: $123,980 (10.3x ROI)
4-Year Net Price (After Aid)
$62,496
-41% less than sticker · See by income
Median Debt at Graduation
$20,556
2.2 months of Year 1 earnings
Reported Earnings (5 Year)
$146,406
31% growth from Year 1

Program Analysis

At $111,560 per year, Computer Engineering graduates from California Polytechnic State University-San Luis Obispo significantly outpace the $78,694 national average for this major, reflecting strong employer demand for this program's graduates.

The 28.7x earnings multiple means ten-year projected earnings exceed tuition cost by an order of magnitude. By pure financial math, this is a standout.

AI exposure is significant at 71% of job tasks, producing a 33% spread between best and worst-case decade earnings. The field isn't immune to disruption.

The median debt load of $20,556 represents less than half a year of starting salary — among the lightest debt-to-income ratios we track.

Ranked #3 out of 174 programs, California Polytechnic State University-San Luis Obispo's Computer Engineering program lands in the top 5% — a strong signal of graduate success.

The five-year earnings trajectory from $111,560 to $146,406 shows 31% growth, reflecting steady but unremarkable salary progression.

About California Polytechnic State University-San Luis Obispo

A 30% acceptance rate puts California Polytechnic State University-San Luis Obispo in competitive admissions territory, with 21,521 students enrolled in San Luis Obispo, CA.

See all programs and financial aid at California Polytechnic State University-San Luis Obispo →

Top Career Paths

Architectural and engineering managers $167,740/yr
Computer hardware engineers $155,020/yr
Database architects $135,980/yr
View all 7 career paths with salary ranges and AI risk →

Compare & Explore

Computer Engineering at Other Schools

Compare Computer Engineering

Other Majors at California Polytechnic State University-San Luis Obispo

Consider the Trade Route?

Trade programs often mean less time in school, lower student debt, and hands-on career paths that tend to be more resilient to AI disruption.

Frequently Asked Questions

How does California Polytechnic State University-San Luis Obispo's Computer Engineering program score?
A score of 87/100 indicates strong financial outcomes. California Polytechnic State University-San Luis Obispo's Computer Engineering graduates fare well on earnings, job market size, and return on investment.
How vulnerable is Computer Engineering to AI automation?
AI won't 'replace' Computer Engineering careers outright, but it is likely to reduce the number of job openings. We model 71% task exposure, which compresses field employment probability in our scenarios.
Why does California Polytechnic State University-San Luis Obispo rank so high for Computer Engineering?
The #3 ranking out of 174 programs is driven by strong financial outcomes — graduates earn well, debt is manageable relative to income, and the job market supports the field.
Scores use College Scorecard earnings, BLS employment projections, and AI task-exposure research. See full methodology →