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  • Machine Learning Engineer

Results for "machine learning engineer"


  • S

    SAS

    SAS Machine Learning Engineer

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Data Preprocessing, Exploratory Data Analysis, Logistic Regression, Statistical Machine Learning, Model Evaluation, Supervised Learning, Decision Tree Learning, Probability & Statistics, Statistics, Machine Learning Software, Classification And Regression Tree (CART), Workflow Management, Predictive Modeling, Random Forest Algorithm, Feature Engineering, SAS (Software), Machine Learning, Applied Machine Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    104 reviews

    Advanced · Professional Certificate · 3 - 6 Months

  • G

    Google Cloud

    Preparing for Google Cloud Certification: Machine Learning Engineer

    Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Generative AI, Google Cloud Platform, Model Deployment, Tensorflow, Big Data, Keras (Neural Network Library), Machine Learning, Data Preprocessing, CI/CD, Model Evaluation, Apache Airflow, Applied Machine Learning, Data Migration, Data Cleansing, Data Quality, Data Lakes, AI Enablement, Cloud Computing

    4.4
    Rating, 4.4 out of 5 stars
    ·
    4.9K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • D
    S

    Multiple educators

    Machine Learning

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing

    4.9
    Rating, 4.9 out of 5 stars
    ·
    38K reviews

    Beginner · Specialization · 1 - 3 Months

  • C

    Coursera

    Train, Tune, & Ship: End-to-End Machine Learning Engineering

    Skills you'll gain: Model Evaluation, Predictive Modeling, Tensorflow, Statistical Machine Learning, MLOps (Machine Learning Operations), Computer Vision, Applied Machine Learning, Performance Testing, Transfer Learning, Keras (Neural Network Library), Performance Tuning, Benchmarking, Feature Engineering, Scikit Learn (Machine Learning Library), Verification And Validation, Network Architecture, Failure Analysis, Deep Learning, PyTorch (Machine Learning Library), Supervised Learning

    Intermediate · Specialization · 1 - 3 Months

  • C

    Coursera

    Gradient to Production: MLOps & Model Serving

    Skills you'll gain: Model Evaluation, MLOps (Machine Learning Operations), Regression Testing, Kubernetes, Docker (Software), Feature Engineering, Containerization, Software Documentation, Data Pipelines, Git (Version Control System), Apache Airflow, Technical Documentation, Microservices, CI/CD, Unit Testing, API Design, Performance Metric, Python Programming, Version Control, Verification And Validation

    Intermediate · Specialization · 3 - 6 Months

  • M

    Microsoft

    Microsoft AI & ML Engineering

    Skills you'll gain: Unsupervised Learning, Model Deployment, Generative AI, Large Language Modeling, Data Management, Natural Language Processing, MLOps (Machine Learning Operations), Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Infrastructure Architecture, LLM Application, Responsible AI, Generative AI Agents, Applied Machine Learning, Azure DevOps, Reinforcement Learning, Data Preprocessing

    4.6
    Rating, 4.6 out of 5 stars
    ·
    352 reviews

    Intermediate · Professional Certificate · 3 - 6 Months

What brings you to Coursera today?

  • P

    Packt

    AI Engineer Professional

    Skills you'll gain: MLOps (Machine Learning Operations), Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Containerization, AI Workflows, Model Evaluation, Model Deployment, Generative AI Agents, LangGraph, Keras (Neural Network Library), Transfer Learning, Artificial Intelligence and Machine Learning (AI/ML), CrewAI, BeeAI, Image Analysis, Deep Learning, Large Language Modeling, Natural Language Processing, Vision Transformer (ViT), Python Programming

    Advanced · Specialization · 1 - 3 Months

  • W

    Whizlabs

    Exam Prep MLA-C01: AWS Machine Learning Engineer Associate

    Skills you'll gain: MLOps (Machine Learning Operations), Feature Engineering, AWS Kinesis, Fraud detection, Amazon Web Services, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Cloud Deployment, 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
    ·
    10 reviews

    Intermediate · Specialization · 3 - 6 Months

  • I

    IBM

    IBM Machine Learning

    Skills you'll gain: Exploratory Data Analysis, Autoencoders, Feature Engineering, Unsupervised Learning, Supervised Learning, Classification Algorithms, Regression Analysis, Dimensionality Reduction, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Deep Learning, Data Analysis, Statistical Methods, Data Preprocessing, Machine Learning, Data Science, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.6K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • D

    Duke University

    MLOps | Machine Learning Operations

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, Responsible AI, Data Manipulation, Exploratory Data Analysis, Containerization, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis

    4.2
    Rating, 4.2 out of 5 stars
    ·
    598 reviews

    Advanced · Specialization · 3 - 6 Months

  • I

    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Apache Spark, PyTorch (Machine Learning Library), Large Language Modeling, Retrieval-Augmented Generation, Transfer Learning, Model Evaluation, Computer Vision, Unsupervised Learning, Generative Model Architectures, Generative AI, PySpark, Vision Transformer (ViT), Keras (Neural Network Library), Supervised Learning, Generative AI Agents, Vector Databases, Machine Learning, Python Programming, Data Science

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    22K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • I

    IBM

    IBM Generative AI Engineering

    Skills you'll gain: Prompt Engineering, Prompt Patterns, Large Language Modeling, LangChain, Retrieval-Augmented Generation, Exploratory Data Analysis, Unsupervised Learning, Generative Model Architectures, PyTorch (Machine Learning Library), ChatGPT, Generative AI, Restful API, LLM Application, Keras (Neural Network Library), Supervised Learning, Generative AI Agents, Model Evaluation, Responsible AI, Vector Databases, Data Import/Export

    4.7
    Rating, 4.7 out of 5 stars
    ·
    99K reviews

    Beginner · Professional Certificate · 3 - 6 Months

1234…649

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

  • SAS Machine Learning Engineer: SAS
  • Preparing for Google Cloud Certification: Machine Learning Engineer: Google Cloud
  • Machine Learning: DeepLearning.AI
  • Train, Tune, & Ship: End-to-End Machine Learning Engineering: Coursera
  • Gradient to Production: MLOps & Model Serving: Coursera
  • Microsoft AI & ML Engineering: Microsoft
  • AI Engineer Professional: Packt
  • Exam Prep MLA-C01: AWS Machine Learning Engineer Associate: Whizlabs
  • IBM Machine Learning: IBM
  • MLOps | Machine Learning Operations: Duke University

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