Results for "machine learning engineering for production"
DeepLearning.AI
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Cloud Deployment, Continuous Deployment, Model Evaluation, Data Preprocessing, Machine Learning, Applied Machine Learning, Data Validation, Feature Engineering, Data Quality, Debugging, Continuous Monitoring, Data Pipelines
Status: Free TrialDuke University
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
Status: NewStatus: Free TrialPragmatic AI Labs
Skills you'll gain: Prompt Engineering, MLOps (Machine Learning Operations), Data Pipelines, Databricks, Generative AI, Data Lakes, Generative AI Agents, Data Governance, Data Architecture, AI Enablement, Data Modeling, Data Management, Data Processing, Data Strategy, Data Quality, Scala Programming, SQL, Python Programming, Data Visualization, Data Literacy
Status: NewStatus: Free TrialKodeKloud
Skills you'll gain: AWS SageMaker, Model Deployment, MLOps (Machine Learning Operations), Data Governance, Data Security, Application Deployment, Personally Identifiable Information, Cloud Deployment, General Data Protection Regulation (GDPR), Continuous Deployment, Model Evaluation, Application Programming Interface (API), Continuous Monitoring
Status: Free TrialGoogle Cloud
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Systems Design, Tensorflow, Hybrid Cloud Computing, Google Cloud Platform, Systems Architecture, Performance Tuning, Machine Learning, Model Evaluation, Distributed Computing, Scalability
Status: Free TrialDuke University
Skills you'll gain: MLOps (Machine Learning Operations), Continuous Delivery, Applied Machine Learning, Google Cloud Platform, Model Deployment, Cloud Applications, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Microsoft Azure, Computer Vision, Application Programming Interface (API), Natural Language Processing, Flask (Web Framework)
What brings you to Coursera today?
Status: Free TrialSkills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Cloud Deployment, Unit Testing, Docker (Software), Containerization, Kubernetes, AI Workflows, IBM Cloud, Microservices, Machine Learning, Responsible AI, Business Metrics, Natural Language Processing, Time Series Analysis and Forecasting, Data Science, Python Programming
Status: NewStatus: Free TrialBoard Infinity
Status: NewStatus: Free TrialSkills you'll gain: MLOps (Machine Learning Operations), Containerization, AI Workflows, Model Deployment, Generative AI Agents, LangGraph, Artificial Intelligence and Machine Learning (AI/ML), CrewAI, BeeAI, Docker (Software), Agentic systems, Google Cloud Platform, AWS SageMaker, CI/CD, Cloud Platforms, DevOps, Azure DevOps Pipelines, Kubernetes, Applied Machine Learning, Scalability
Status: NewStatus: Free TrialSkills 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
Status: NewStatus: Free TrialSkills you'll gain: Model Evaluation, Model Deployment, Data Preprocessing, MLOps (Machine Learning Operations), Data Cleansing, Microservices, Data Pipelines, Feature Engineering, Data Quality, Data Validation, Containerization, Application Deployment, Service Level, Extract, Transform, Load, Data Transformation, System Monitoring, Debugging, Machine Learning Methods, Performance Tuning, Machine Learning Algorithms
Status: NewStatus: Free TrialSkills 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
In summary, here are 10 of our most popular machine learning engineering for production courses
- Machine Learning in Production: DeepLearning.AI
- MLOps | Machine Learning Operations: Duke University
- Enterprise AI and Data Engineering with Databricks: Pragmatic AI Labs
- Deploy ML Models to Production: KodeKloud
- Production Machine Learning Systems: Google Cloud
- Cloud Machine Learning Engineering and MLOps: Duke University
- AI Workflow: AI in Production: IBM
- MLOps and LLMOps: Deploying and Scaling AI in Production: Board Infinity
- AI Agents and MLOps for Production-Ready AI: Packt
- Gradient to Production: MLOps & Model Serving: Coursera
