MLS-C01AWS Certified Machine Learning - Specialty is retired
Original questions written from the published objectives and cited to official documentation, never recalled exam content. How we verify, why not dumps.
- Exam code
- MLS-C01
- Cost
- $300USD
- Questions
- 65(50 scored, 15 unscored)
- Duration
- 180minutes
- Passing score
- 750(scale 100-1000)
- Level
- Advanced
- Study guide
- How to prepare
- Format
- Multiple choice and multiple response
What the exam tests
Exam domains and official weightings
The percentage is the exam weighting; the bar is how many verified questions we hold there, so a short bar is where our bank is thin.
- Data Engineering20%0 verified
- Exploratory Data Analysis24%0 verified
- Modeling36%0 verified
- Machine Learning Implementation and Operations20%0 verified
What the exam actually asks you to do
Multiple choice and multiple response only. No simulations, no labs, and nothing to configure.
Item formats
- Multiple choice
- Multiple response
Nothing here needs a lab. Reading carefully and eliminating options is the whole skill. AWS, Machine Learning Specialty exam guide ↗
Amazon Web Services (AWS)’s free resources
Study from the source. The page below is free to read, and it is what our own questions are written from.
Official Machine Learning Specialty exam page & objectives ↗Keep reading
- Machine Learning Specialty exam format
How many questions, how long, what the items look like, and how long it stays valid.
- Machine Learning Specialty passing score
The exact cut score, what kind of number it is, and the retake terms.
- How hard is Machine Learning Specialty?
An honest difficulty read from the format, the clock and the weights.
Frequently asked questions
How mathematical is MLS-C01?
Conceptually mathematical, not computationally. You will not derive gradients, but you must know why precision beat recall for a described problem, what regularization changes and which algorithm fits a data shape. Modeling alone is 36%.
MLS or the newer ML Engineer Associate?
MLA-C01 covers building and operating pipelines; MLS-C01 adds theory depth: algorithm internals, tuning strategy and evaluation design. Practitioners increasingly take MLA first and MLS when the role demands the theory.
How much of the exam is SageMaker?
A large share. Built-in algorithms, training configuration, endpoint options and debugging appear constantly, with the classic data services (Kinesis, Glue, S3) carrying the data engineering domain.