Results for "ml deployment challenges"
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Apache Airflow, Data Pipelines, Apache Kafka, DevOps, CI/CD, Apache Spark, Pandas (Python Package), Deep Learning, Applied Machine Learning, Machine Learning, Data Governance, Supervised Learning, Flask (Web Framework), Grafana, Python Programming, Automation, Unsupervised Learning, Continuous Monitoring
Skills you'll gain: Model Deployment, AWS SageMaker, Data Pipelines, Apache Airflow, MLOps (Machine Learning Operations), Systems Design, Cloud Computing Architecture, Transfer Learning, Model Evaluation, Cloud Deployment, PyTorch (Machine Learning Library), Cloud Computing, Network Architecture, Unit Testing, API Design, Deep Learning, Python Programming, Data Validation, CI/CD, Keras (Neural Network Library)
KodeKloud
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
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Application Deployment, Cloud Deployment, Continuous Deployment, Containerization, Docker (Software), DevOps, Release Management, Version Control, Dependency Analysis, Performance Tuning, CI/CD, Performance Testing, Package and Software Management, Performance Analysis, Performance Metric, Application Performance Management, Application Development, Cost Benefit Analysis
Skills 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
Skills you'll gain: MLOps (Machine Learning Operations), Continuous Integration, Artificial Intelligence and Machine Learning (AI/ML), DevOps, Service Level Agreement, API Design, Performance Measurement, Performance Analysis
What brings you to Coursera today?
Microsoft
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
Coursera
Skills you'll gain: Model Deployment, Unit Testing, MLOps (Machine Learning Operations), Test Driven Development (TDD), Software Testing, Scalability, Dashboard, Continuous Integration, Testability, Kubernetes, CI/CD, Performance Tuning, Software Engineering, PyTorch (Machine Learning Library), Docker (Software), Tensorflow, Containerization, Scikit Learn (Machine Learning Library), Git (Version Control System), Python Programming
Skills you'll gain: MLOps (Machine Learning Operations), Version Control, Model Deployment, CI/CD, Git (Version Control System), Continuous Deployment, Performance Tuning, Continuous Integration, Software Development Methodologies, Software Versioning, Release Management, Continuous Delivery, PyTorch (Machine Learning Library), Performance Improvement, Software Testing
Pragmatic AI Labs
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Hugging Face, Rust (Programming Language), Cloud Deployment, Application Deployment, CI/CD, Performance Tuning, Large Language Modeling, Performance Testing, Cross Platform Development, Cryptography
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Generative AI, Dependency Analysis, Dashboard, Application Deployment, Continuous Deployment, System Monitoring, Responsible AI, Performance Tuning, Site Reliability Engineering, Release Management, Kubernetes, Application Performance Management, CI/CD, Performance Analysis, Continuous Monitoring, Automation, Cloud Platforms, Data-Driven Decision-Making
Coursera
Skills you'll gain: Model Deployment, Docker (Software), Containerization, Cloud Deployment, MLOps (Machine Learning Operations), Hugging Face, Generative AI, Cloud Computing Architecture, Serverless Computing, Cloud Hosting, Cloud Technologies, AWS SageMaker, System Monitoring, Release Management, Application Security, Infrastructure Security, Continuous Monitoring, Version Control
In summary, here are 10 of our most popular ml deployment challenges courses
- Hands-On MLOps Fundamentals for ML Engineers: KodeKloud
- AI Model Development & Deployment: Coursera
- Deploy ML Models to Production: KodeKloud
- Deploy, Evaluate and Create AI Systems: Coursera
- AI Agents and MLOps for Production-Ready AI: Packt
- Deploy & Optimize ML Services Confidently: Coursera
- Microsoft AI & ML Engineering: Microsoft
- ML Production Systems: Coursera
- Optimize and Manage Your ML Codebase: Coursera
- Production ML with Hugging Face: Pragmatic AI Labs
