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  • Machine Learning Engineering

Results for "machine learning engineering"


  • Status: New
    New
    Status: Free Trial
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    S

    SAS

    SAS Machine Learning Engineer

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Data Preprocessing, Classification And Regression Tree (CART), Exploratory Data Analysis, Logistic Regression, Statistical Machine Learning, Model Evaluation, Model Training, Supervised Learning, Decision Tree Learning, Probability & Statistics, Data Processing, Machine Learning Software, Statistical Software, Machine Learning Methods, Process Modeling, Machine Learning, Correlation Analysis, Applied Machine Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    105 reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
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    D

    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Linear Algebra, Statistical Inference, Model Optimization, Machine Learning Methods, Statistics, Applied Mathematics, Probability, Calculus, Dimensionality Reduction, Applied Machine Learning, Mathematical Software, Data Transformation, Machine Learning

    4.6
    Rating, 4.6 out of 5 stars
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    3.2K reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: New
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    C

    Coursera

    Data Engineering & Pipeline Reliability for Machine Learning

    Skills you'll gain: Data Preprocessing, Data Cleansing, Data Pipelines, Feature Engineering, Data Quality, MLOps (Machine Learning Operations), Extract, Transform, Load, Data Transformation, Data Integration, Dataflow, Development Environment, Data Wrangling, Apache Airflow, Package and Software Management, Git (Version Control System), Quality Assurance, Exploratory Data Analysis, Cost Management, Resource Utilization, Virtual Environment

    Intermediate · Course · 1 - 3 Months

  • Status: New
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    K

    KodeKloud

    Data Engineering Essentials

    Skills you'll gain: MLOps (Machine Learning Operations), Apache Kafka, Apache Airflow, Apache Spark, Extract, Transform, Load, Data Lakes, Data Pipelines, Distributed Computing, Real Time Data, DevOps, Data Processing, Feature Engineering, CI/CD, Pandas (Python Package), Continuous Integration

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Mathematics for Machine Learning

    Skills you'll gain: Dimensionality Reduction, Linear Algebra, Regression Analysis, NumPy, Calculus, Data Preprocessing, Unsupervised Learning, Feature Engineering, Applied Mathematics, Model Optimization, Mathematical Software, Jupyter, Statistics, Numerical Analysis, Applied Machine Learning, Artificial Neural Networks, Data Science, Data Manipulation, Python Programming, Data Transformation

    4.6
    Rating, 4.6 out of 5 stars
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    15K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: New
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    Status: Free Trial
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    C

    Coursera

    Production-Ready Multimodal ML Engineering

    Skills you'll gain: MLOps (Machine Learning Operations), Data Validation, Model Deployment, Test Driven Development (TDD), Apache Airflow, Data Pipelines, Containerization, Extract, Transform, Load, Kubernetes, Model Training, Data Integrity, Model Optimization, Cloud-Native Computing, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Software, Artificial Intelligence, Artificial Neural Networks, Machine Learning Algorithms, Natural Language Processing, Algorithms

    Intermediate · Course · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    W

    Whizlabs

    Exam Prep MLA-C01: AWS Machine Learning Engineer Associate

    Skills you'll gain: MLOps (Machine Learning Operations), Feature Engineering, Model Optimization, AWS Kinesis, Fraud detection, Amazon Web Services, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Data Cleansing, Data Processing, Data Wrangling, Data Integrity, Machine Learning, Machine Learning Algorithms, Data Modeling, Supervised Learning, Data Mining, Random Forest Algorithm, Data Management, Unsupervised Learning

    3.9
    Rating, 3.9 out of 5 stars
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    10 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
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    C

    Coursera

    Training, Evaluating, and Monitoring Machine Learning Models

    Skills you'll gain: Model Evaluation, Model Training, MLOps (Machine Learning Operations), System Monitoring, Continuous Monitoring, Model Deployment, Verification And Validation, Performance Metric, A/B Testing, Statistical Methods, Failure Analysis, Statistical Hypothesis Testing, Applied Machine Learning, Statistical Analysis, Scikit Learn (Machine Learning Library), Benchmarking

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Machine Learning on Google Cloud

    Skills you'll gain: Feature Engineering, Model Optimization, Generative AI, Model Deployment, Tensorflow, Generative AI Agents, Google Gemini, Model Training, Keras (Neural Network Library), Machine Learning, Generative Model Architectures, Data Preprocessing, Machine Learning Software, MLOps (Machine Learning Operations), Google Cloud Platform, Model Evaluation, Applied Machine Learning, Data Cleansing, Data Quality, Cloud Computing

    4.4
    Rating, 4.4 out of 5 stars
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    3.8K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
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    Status: Free Trial
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    C

    Coursera

    Deploying and Debugging ML Microservices

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Microservices, Containerization, Application Deployment, Service Level, Debugging, Unit Testing, Software Testing, System Monitoring, Continuous Deployment, Docker (Software), Software Architecture, Kubernetes, Software Design, Restful API, Systems Architecture, Cloud Computing Architecture, Application Performance Management, Continuous Monitoring

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Building, Optimizing, and Validating Machine Learning Models

    Skills you'll gain: Model Training, Model Optimization, Model Evaluation, Machine Learning Software, Applied Machine Learning, Predictive Modeling, Machine Learning Methods, Feature Engineering, Verification And Validation, Workflow Management, Machine Learning, Supervised Learning, Statistical Machine Learning, Statistical Modeling, Scikit Learn (Machine Learning Library), Benchmarking, Random Forest Algorithm, Performance Analysis, Cost Management, Resource Utilization

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Applied Machine Learning

    Skills you'll gain: Computer Vision, Model Evaluation, PyTorch (Machine Learning Library), Supervised Learning, Unsupervised Learning, Image Analysis, Applied Machine Learning, Data Preprocessing, Dimensionality Reduction, Machine Learning Methods, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Convolutional Neural Networks, Regression Analysis, Data Processing, Model Training, Machine Learning, Deep Learning, Model Optimization

    3.4
    Rating, 3.4 out of 5 stars
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    16 reviews

    Intermediate · Specialization · 3 - 6 Months

1234…834

In summary, here are 10 of our most popular machine learning engineering courses

  • SAS Machine Learning Engineer: SAS
  • Mathematics for Machine Learning and Data Science: DeepLearning.AI
  • Data Engineering & Pipeline Reliability for Machine Learning: Coursera
  • Data Engineering Essentials: KodeKloud
  • Mathematics for Machine Learning: Imperial College London
  • Production-Ready Multimodal ML Engineering: Coursera
  • Exam Prep MLA-C01: AWS Machine Learning Engineer Associate: Whizlabs
  • Training, Evaluating, and Monitoring Machine Learning Models: Coursera
  • Machine Learning on Google Cloud: Google Cloud
  • Deploying and Debugging ML Microservices: Coursera

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