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    Free Practice Questions for Cloudera Machine Learning Engineer (CDP-6001) Certification

    Guide checked for updates:
    19 Sep 2026
    Question bank created:
    7 Jul 2026
    Question bank last updated:
    11 Aug 2026

    Study with 358 exam-style practice questions designed to help you prepare for the Cloudera Machine Learning Engineer (CDP-6001).

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    Exam Details

    Key information about Cloudera Machine Learning Engineer (CDP-6001)

    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)

    1: Cloudera Machine Learning

    1.1: Workspaces

    Workspaces

    1.2: Projects

    Projects

    1.3: Experiments

    Experiments

    1.4: Accelerators for ML Projects

    Accelerators for ML Projects

    1.5: Data Visualizations

    Data Visualizations

    1.6: Runtimes

    Runtimes

    1.7: GPUs

    GPUs

    2: Spark

    2.1: DataFrames

    DataFrames

    2.2: File Types

    File Types

    2.3: Window Functions

    Window Functions

    3: Spark MLLib

    3.1: Model Selection and Tuning

    Model Selection and Tuning

    3.2: Fitting and Evaluating Models

    Fitting and Evaluating Models

    3.3: Pipelines

    Pipelines

    4: Deploying a Machine Learning Model

    4.1: Applications/API

    Applications/API

    4.2: Autoscaling and Performance

    Autoscaling and Performance

    4.3: Model Metrics and Monitoring

    Model Metrics and Monitoring

    4.4: ML Flow

    ML Flow

    5: Deep Learning and General Machine Learning

    5.1: Learning

    Learning

    5.2: General Machine Learning

    General Machine Learning

    5.3: Supervised and unsupervised learning

    Supervised and unsupervised learning

    5.4: Algorithms

    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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