AWS Machine Learning Specialty (MLS-C01) vs Google Cloud Professional Data Engineer
| Factor | ✅ AWS Machine Learning Specialty (MLS-C01) | Google Cloud Professional Data Engineer |
|---|---|---|
| Vendor | Amazon Web Services | Google Cloud |
| Level | Advanced | Advanced |
| Exam Cost | $300 | $200 |
| Pass Rate | 55% | 55% |
| Avg Salary | $145K–$180K | $145K–$175K |
| Difficulty |
Hard
★★★★☆
|
Hard
★★★★☆
|
| Best For | Data scientists and ML engineers with 1+ year of ML experience on AWS. | Data engineers and ML engineers with solid GCP experience building production pi… |
| Expiry | Typically 3 years — renewal at aws.amazon.com | Check cloud.google.com |
| Full Guide | View guide → | View guide → |
Which Should You Choose?
The right certification depends on your current role, target employer, geography, and the specific skills gap you're trying to close. Here's a practical breakdown:
✅ Choose AWS Machine Learning Specialty (MLS-C01) if…
You're targeting roles at organisations that specifically require Amazon Web Services credentials, or you're already working within the Amazon Web Services ecosystem. The AWS Machine Learning Specialty (MLS-C01) carries the strongest recognition among Amazon Web Services customers and partners, and its salary premium of $145K–$180K is well-documented in the job market.
Full Guide →Consider Google Cloud Professional Data Engineer if…
You're targeting organisations in the Google Cloud ecosystem, or the Google Cloud Professional Data Engineer is more commonly required in your target industry or geography. Salary data: $145K–$175K. Validates expertise in designing and building data processing systems and machine learning models on…
Full Guide →Detailed Analysis — AWS Machine Learning Specialty (MLS-C01)
Strengths
- ✓Issued by Amazon Web Services — one of the most trusted credential authorities in Data & AI
- ✓Salary premium of $145K–$180K documented across multiple independent sources
- ✓Exam fee of $300 — strong ROI relative to salary gain
- ✓Global recognition at enterprise employers, government agencies, and consulting firms
- ✓Covers 5 core domains including: Data engineering for ML, Exploratory data analysis, Modeling techniques
Considerations
- ◆Pass rate is approximately 55% — structured preparation is essential, not optional
- ◆Requires significant hands-on experience — not suitable for complete beginners
- ◆Renewal required — check current requirements at aws.amazon.com
Made your decision? Start your preparation today.
AWS Machine Learning Specialty (MLS-C01) Full Guide → Study Roadmap → Salary Data →