AWS Machine Learning Specialty (MLS-C01)
How to prepare for MLS-C01
A 5-stage plan from your first study session to exam day. Adjust the pace to your own schedule.
Study plan
| Stage | What to do | Time |
|---|---|---|
| 1 | Understand the Exam Blueprint Read the official exam guide and note the high‑level domains and question style (multiple‑choice/multiple‑response). | Week 1 |
| 2 | Fill Knowledge Gaps Take digital courses, Builder Labs, and Cloud Quest to strengthen AWS ML services knowledge. | Weeks 2‑3 |
| 3 | Hands‑On Practice Complete AWS Builder Labs, SimuLearn, and SageMaker labs to build, train, and deploy real models. | Weeks 4‑5 |
| 4 | Exam‑Style Drills Use the Official Practice Question Set and flashcards; simulate the 180‑minute, 65‑question format. | Week 6 |
| 5 | Final Review & Scheduling Review any weak areas, confirm you meet the 2‑year experience baseline, and schedule the Pearson VUE or online proctored exam. | Week 7 |
Exam domains
These come from the official exam outline.
- Data engineering for ML
- Exploratory data analysis
- Modeling techniques
- ML implementation & operations
- AWS ML services (SageMaker, Rekognition, Comprehend)
MLS-C01 preparation questions
How many steps are in the MLS-C01 study plan?
This plan has 5 stages, starting with understand the Exam Blueprint and ending with final Review & Scheduling.
Do I need prior experience for MLS-C01?
2+ years experience developing, architecting, and running ML or deep learning workloads in the AWS Cloud; candidates often hold an AWS Associate or Professional certification
What should I study for MLS-C01?
Focus on the official exam domains: Data engineering for ML, Exploratory data analysis, Modeling techniques, ML implementation & operations, AWS ML services (SageMaker, Rekognition, Comprehend).
Exam outlines change between versions. Check the official exam page for the current outline before you start.