Results for "ml deployment challenges"
Status: NewStatus: Free TrialSkills 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
Status: Free TrialMicrosoft
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
Status: NewStatus: Free TrialSkills you'll gain: AWS SageMaker, Systems Design, Cloud Computing Architecture, MLOps (Machine Learning Operations), Model Deployment, Cloud Computing, Network Architecture, API Design, Transfer Learning, PyTorch (Machine Learning Library), Deep Learning, Keras (Neural Network Library), Performance Tuning, Model Evaluation, CI/CD, Data Pipelines, Software Engineering, Python Programming, Unit Testing, Data Validation
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 Trial
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
What brings you to Coursera today?
Status: NewStatus: Free TrialCoursera
Skills you'll gain: Unit Testing, Test Driven Development (TDD), Software Testing, Scalability, Dashboard, MLOps (Machine Learning Operations), Testability, Kubernetes, Version Control, Model Deployment, Performance Tuning, Software Engineering, PyTorch (Machine Learning Library), Tensorflow, CI/CD, Containerization, Docker (Software), Scikit Learn (Machine Learning Library), Git (Version Control System), Python Programming
Status: New
Status: NewStatus: Free TrialPragmatic 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
Status: NewStatus: Free TrialSkills 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
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: NewStatus: Free TrialSkills 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
In summary, here are 10 of our most popular ml deployment challenges courses
- Deploy, Evaluate and Create AI Systems: Coursera
- Microsoft AI & ML Engineering: Microsoft
- AI Model Development & Deployment: Coursera
- MLOps | Machine Learning Operations: Duke University
- Deploy & Optimize ML Services Confidently: Coursera
- AI Agents and MLOps for Production-Ready AI: Packt
- ML Production Systems: Coursera
- Chroma, Weaviate & Production RAG Deployment: Coursera
- Production ML with Hugging Face: Pragmatic AI Labs
- Optimize and Manage Your ML Codebase: Coursera
