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  • Mlops

MLOps Courses

MLOps courses can help you learn deployment strategies, model monitoring, and continuous integration and delivery for machine learning projects. You can build skills in automating workflows, managing data pipelines, and ensuring compliance with governance standards. Many courses introduce tools like TensorFlow, Kubernetes, and MLflow, that support operationalizing AI models and streamlining collaboration between data scientists and IT teams.


Popular MLOps Courses and Certifications


  • G

    Google Cloud

    AI Infrastructure: Storage Options

    Skills you'll gain: Data Infrastructure, Model Training, Data Preprocessing, Model Deployment, Data Storage Technologies, Data Processing, Model Optimization, AI Workflows, Data Persistence, Data Pipelines, Data Access, File Systems

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    Advanced RAG Patterns

    Skills you'll gain: Retrieval-Augmented Generation, Prompt Patterns, Agentic systems, Performance Testing, Prompt Engineering, Generative AI Agents, Generative AI, Agentic Workflows, Performance Tuning, Model Evaluation, Verification And Validation, Large Language Modeling, MLOps (Machine Learning Operations), Embeddings

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Optimize Vision Datasets: Augment and Analyze

    Skills you'll gain: Transfer Learning, Model Training, Model Optimization, Image Quality, Computer Vision, Image Analysis, Data Pipelines, Data Transformation, Data Manipulation, Exploratory Data Analysis, Artificial Intelligence and Machine Learning (AI/ML)

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Deploy, Evaluate and Create AI Systems

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Application Deployment, Cloud Deployment, Continuous Deployment, Containerization, Docker (Software), DevOps, Release Management, Version Control, Continuous Delivery, Dependency Analysis, Performance Tuning, Performance Testing, Package and Software Management, Performance Analysis, Performance Metric, Application Performance Management, Application Development, Cost Benefit Analysis

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Optimize AI: Build Reusable Model Pipelines

    Skills you'll gain: Model Optimization, Model Deployment, AI Workflows, Scikit Learn (Machine Learning Library), Model Evaluation, Data Preprocessing, Version Control

    Intermediate · Course · 1 - 4 Weeks

  • G

    Google Cloud

    Introduction to AI and Machine Learning on GC - 简体中文

    Skills you'll gain: Prompt Engineering, Generative AI, Generative AI Agents, Google Cloud Platform, MLOps (Machine Learning Operations), Cloud Infrastructure, AI Workflows, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Model Training, Artificial Intelligence, Model Deployment, Machine Learning, No-Code Development, Application Deployment

    Beginner · Course · 1 - 3 Months

  • C

    Coursera

    Choose Optimal Data Structures for ML

    Skills you'll gain: Data Structures, Feature Engineering, MLOps (Machine Learning Operations), Java Programming, Java, Performance Tuning, Data Processing, Applied Machine Learning, System Monitoring, Scalability, Performance Analysis, Memory Management, Benchmarking, Graph Theory, Program Implementation

    Advanced · Course · 1 - 4 Weeks

  • W

    Whizlabs

    AWS: ML Workflows with SageMaker, Storage & Security

    Skills you'll gain: AWS SageMaker, AWS Kinesis, Amazon Web Services, Amazon Redshift, Cloud Security, MLOps (Machine Learning Operations), Amazon S3, Model Training, AWS Identity and Access Management (IAM), Model Deployment, Real Time Data, Feature Engineering, Cloud Storage, Data Storage, Data Security, Encryption, Key Management

    Intermediate · Course · 1 - 4 Weeks

  • G

    Google Cloud

    ML Pipelines on Google Cloud - 日本語版

    Skills you'll gain: Google Cloud Platform, CI/CD, MLOps (Machine Learning Operations), Data Pipelines, Tensorflow, Continuous Deployment, Model Deployment, Model Training, Metadata Management, AI Orchestration, PyTorch (Machine Learning Library)

    Advanced · Course · 1 - 3 Months

  • C

    Coursera

    Building Reliable LLM Systems

    Skills you'll gain: LLM Application, Model Evaluation, Large Language Modeling, Retrieval-Augmented Generation, Vector Databases, MLOps (Machine Learning Operations), Performance Tuning, Debugging, Performance Testing, Statistical Methods, Query Languages, SQL, Statistical Hypothesis Testing, Statistical Analysis, Artificial Intelligence and Machine Learning (AI/ML), Data-Driven Decision-Making, Python Programming

    Intermediate · Course · 1 - 3 Months

  • G

    Google Cloud

    Uptraining with Document AI Workbench

    Skills you'll gain: Model Training, Google Cloud Platform, Data Processing, Document Management, MLOps (Machine Learning Operations)

    Intermediate · Project · Less Than 2 Hours

  • C

    Coursera

    Optimize Deep Learning: Tune PyTorch Models

    Skills you'll gain: Fine-tuning, Model Optimization, Model Deployment, Model Training, PyTorch (Machine Learning Library), Transfer Learning, Performance Tuning, Debugging, MLOps (Machine Learning Operations), Deep Learning, Scalability, Artificial Neural Networks

    Intermediate · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular mlops courses

  • AI Infrastructure: Storage Options: Google Cloud
  • Advanced RAG Patterns: Coursera
  • Optimize Vision Datasets: Augment and Analyze: Coursera
  • Deploy, Evaluate and Create AI Systems: Coursera
  • Optimize AI: Build Reusable Model Pipelines: Coursera
  • Introduction to AI and Machine Learning on GC - 简体中文: Google Cloud
  • Choose Optimal Data Structures for ML: Coursera
  • AWS: ML Workflows with SageMaker, Storage & Security : Whizlabs
  • ML Pipelines on Google Cloud - 日本語版: Google Cloud
  • Building Reliable LLM Systems: Coursera

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