Results for "mlops engineer"
Microsoft
Skills you'll gain: Unsupervised Learning, Fine-tuning, Model Deployment, Generative AI, Large Language Modeling, Data Management, Generative Model Architectures, 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, Data Preprocessing, Model Optimization
Duke University
Skills you'll gain: Pandas (Python Package), MLOps (Machine Learning Operations), NumPy, Unit Testing, Model Deployment, Data Manipulation, Test Script Development, Software Testing, Data Import/Export, Applied Machine Learning, Test Automation, Data Wrangling, Python Programming, Code Reusability, Data Processing, Debugging, Data Structures, Machine Learning, Object Oriented Programming (OOP), Scripting
Microsoft
Skills you'll gain: Responsible AI, MLOps (Machine Learning Operations), Azure DevOps Pipelines, Azure DevOps, Generative AI, Microsoft Azure, Model Deployment, AI Workflows, Model Training, CI/CD, Version Control, Data Ethics, Artificial Intelligence, Model Evaluation, Continuous Integration, Git (Version Control System), Automation, Application Performance Management, Continuous Monitoring
Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Model Deployment, AI Orchestration, AI Workflows, Generative AI, Google Cloud Platform, Data Modeling, Continuous Monitoring, Data Pipelines, Model Training, Feature Engineering, Model Optimization, DevOps, Agentic Workflows, Generative AI Agents, Data Store, Continuous Deployment, Data Preprocessing, Forecasting
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Model Training, Amazon Web Services, Apache Airflow, Data Pipelines, Apache Kafka, DevOps, CI/CD, Apache Spark, Pandas (Python Package), Deep Learning, Machine Learning, Data Governance, Supervised Learning, Flask (Web Framework), Grafana, Python Programming, Automation, Unsupervised Learning
Duke University
Skills you'll gain: Fine-tuning, MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, GitHub Copilot, Unit Testing, Responsible AI, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis
What brings you to Coursera today?
Skills you'll gain: Feature Engineering, Model Evaluation, Model Deployment, Fine-tuning, Data Preprocessing, Model Training, Deep Learning, Machine Learning Methods, Model Optimization, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Scalability, Hugging Face, Docker (Software), Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Application Deployment, Software Development, Machine Learning
Skills you'll gain: Model Training, Fine-tuning, Model Evaluation, Model Optimization, Machine Learning Methods, Predictive Modeling, Tensorflow, Statistical Machine Learning, Machine Learning Software, MLOps (Machine Learning Operations), Computer Vision, Performance Testing, Transfer Learning, Feature Engineering, Scikit Learn (Machine Learning Library), Verification And Validation, Network Architecture, Deep Learning, Benchmarking, PyTorch (Machine Learning Library)
Pragmatic AI Labs
Skills you'll gain: Databricks, Role-Based Access Control (RBAC), MLOps (Machine Learning Operations), Data Lakes, Data Governance, CI/CD, Authorization (Computing), Anomaly Detection, Identity and Access Management, Model Deployment, Generative AI, Data Access, Metadata Management, Data Engineering, Data Quality, GitHub, Event Monitoring, Test Tools, Authentications, Python Programming
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
Skills you'll gain: Model Evaluation, Model Deployment, Model Training, Model Optimization, Data Preprocessing, MLOps (Machine Learning Operations), Data Cleansing, Microservices, Data Pipelines, Feature Engineering, Data Quality, Containerization, Application Deployment, Service Level, Extract, Transform, Load, Data Transformation, System Monitoring, Machine Learning Methods, Performance Tuning, Machine Learning Algorithms
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Google Cloud Platform, Model Evaluation, Model Training, DevOps, Continuous Deployment, CI/CD, AI Workflows, Automation
In summary, here are 10 of our most popular mlops engineer courses
- Microsoft AI & ML Engineering:Â Microsoft
- Python Essentials for MLOps:Â Duke University
- MLOps and responsible AI practices:Â Microsoft
- Machine Learning Operations (MLOps) on Google Cloud:Â Google Cloud
- Hands-On MLOps Fundamentals for ML Engineers:Â KodeKloud
- MLOps | Machine Learning Operations:Â Duke University
- Machine Learning and Deep Learning for Software Engineers:Â Board Infinity
- Train, Tune, & Ship: End-to-End Machine Learning Engineering:Â Coursera
- Production Governance and MLOps on Databricks:Â Pragmatic AI Labs
- Gradient to Production: MLOps & Model Serving:Â Coursera
