Free Practice Questions for Cloudera Machine Learning Engineer (CLOUDERA-MACHINE-LEARNING-ENGINEER) Certification

    🔄 Last checked for updates July 7th, 2026

    Study with 364 exam-style practice questions designed to help you prepare for the Cloudera Machine Learning Engineer (CLOUDERA-MACHINE-LEARNING-ENGINEER).

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    Exam Details

    Key information about Cloudera Machine Learning Engineer (CLOUDERA-MACHINE-LEARNING-ENGINEER)

    Official study guide

    View

    Question formats CertSafari offers
    • Multiple choice
    exam code:

    CDP-6001

    passing score:

    60%

    delivery method:

    Online, proctored

    target audience:

    Machine Learning Engineers, MLOps professionals, Data Scientists

    allowed resources:

    None

    time limit minutes:

    90

    number of questions:

    45

    Exam Topics & Skills Assessed

    Skills measured (from the official study guide)

    Cloudera Machine Learning(31%)

    Workspaces

    • Workspaces management

    Projects

    • Project organization

    Experiments

    • Experiment tracking

    Accelerators for ML Projects

    • ML project accelerators

    Data Visualizations

    • Data visualization tools

    Runtimes

    • Runtime environments

    GPUs

    • GPU utilization

    Spark(18%)

    DataFrames

    • Spark DataFrames

    File Types

    • Spark file type handling

    Window Functions

    • Spark Window Functions

    Spark MLLib(22%)

    Model Selection and Tuning

    • Model selection
    • Model tuning

    Fitting and Evaluating Models

    • Model fitting
    • Model evaluation

    Pipelines

    • ML Pipelines

    Deploying a Machine Learning Model(18%)

    Applications/API

    • Application deployment
    • API integration

    Autoscaling and Performance

    • Autoscaling models
    • Performance optimization

    Model Metrics and Monitoring

    • Model metrics
    • Model monitoring

    ML Flow

    • ML Flow for model lifecycle

    Deep Learning and General Machine Learning(11%)

    Learning

    • Machine learning concepts

    General Machine Learning

    • General ML techniques

    Supervised and unsupervised learning

    • Supervised learning
    • Unsupervised learning

    Algorithms

    • Machine learning algorithms
    • Deep learning algorithms

    Techniques & products

    Cloudera Data Platform (CDP)
    Cloudera Machine Learning (CML)
    Spark
    Spark MLLib
    MLOps
    Data Modeling
    Data Science Concepts
    Machine Learning Models
    Model Deployment
    Model Tuning
    DataFrames
    File Types
    Window Functions
    Model Selection
    Model Evaluation
    Pipelines
    Applications
    APIs
    Autoscaling
    Performance Optimization
    Model Metrics
    Model Monitoring
    ML Flow
    Deep Learning
    Supervised Learning
    Unsupervised Learning
    Machine Learning Algorithms
    Workspaces
    Projects
    Experiments
    Accelerators for ML Projects
    Data Visualizations
    Runtimes
    GPUs

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