Results for "hybrid cloud computing machine learning"
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: 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 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: Cloud Security, Hybrid Cloud Computing, Cloud Computing Architecture, Cloud Engineering, Infrastructure as Code (IaC), Restful API, Cloud Computing, Application Deployment, Microservices, Disaster Recovery, Cloud Infrastructure, CI/CD, Kubernetes, Containerization, Cloud Deployment, Cloud Services, Multi-Cloud, Solution Architecture, Docker (Software), Application Design
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
Google Cloud
Skills you'll gain: Feature Engineering, Model Optimization, Generative AI, Model Deployment, Tensorflow, Generative AI Agents, Google Gemini, Model Training, Keras (Neural Network Library), Machine Learning, Generative Model Architectures, Data Preprocessing, Machine Learning Software, Machine Learning Methods, MLOps (Machine Learning Operations), Google Cloud Platform, Model Evaluation, Data Cleansing, Data Quality, Cloud Computing
What brings you to Coursera today?
University of Pittsburgh
Skills you'll gain: Apache Hadoop, Cloud Computing, Cloud Deployment, Apache Spark, Web Services, Cloud Technologies, Cloud Services, Virtualization and Virtual Machines, Cloud Computing Architecture, PySpark, Cloud Infrastructure, Cloud Development, Distributed Computing, Data Processing, Cloud Storage, Docker (Software), Virtualization, Containerization, Restful API, Data Architecture
Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Model Optimization, Generative AI, Google Cloud Platform, Model Deployment, Tensorflow, Generative AI Agents, Google Gemini, Model Training, Dataflow, Big Data, Keras (Neural Network Library), Machine Learning, Generative Model Architectures, Data Preprocessing, Machine Learning Software, CI/CD, Machine Learning Methods, Cloud Computing
Microsoft
Skills you'll gain: Unsupervised Learning, Microsoft Azure, Applied Machine Learning, Machine Learning Software, Model Training, Regression Analysis, Predictive Modeling, Machine Learning, No-Code Development, Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Model Deployment, Artificial Intelligence, Classification Algorithms, Supervised Learning
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Microservices, Containerization, Application Deployment, Service Level, Debugging, Unit Testing, Software Testing, System Monitoring, Continuous Deployment, Docker (Software), Software Architecture, Kubernetes, Software Design, Restful API, Systems Architecture, Cloud Computing Architecture, Application Performance Management, Continuous Monitoring
Google Cloud
Skills you'll gain: Model Deployment, Model Optimization, Convolutional Neural Networks, Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Large Language Modeling, Reinforcement Learning, Model Training, Transfer Learning, Computer Vision, Keras (Neural Network Library), Systems Design, Applied Machine Learning, Image Analysis, AI Personalization, Cloud Deployment, Recurrent Neural Networks (RNNs), Machine Learning
Skills you'll gain: Apache Spark, Machine Learning, Generative AI, Model Evaluation, Supervised Learning, Apache Hadoop, Data Pipelines, Unsupervised Learning, Data Processing, Extract, Transform, Load, Predictive Modeling, Model Deployment, Classification Algorithms, Data Transformation, Regression Analysis
In summary, here are 10 of our most popular hybrid cloud computing machine learning courses
- Machine Learning and Deep Learning for Software Engineers: Board Infinity
- Machine Learning Operations (MLOps) on Google Cloud: Google Cloud
- Machine Learning Made Easy for Software Engineers: Coursera
- Hybrid Cloud Capstone Project : IBM
- MLOps | Machine Learning Operations: Duke University
- Machine Learning on Google Cloud: Google Cloud
- Cloud Computing for Data Science: University of Pittsburgh
- Preparing for Google Cloud Certification: Machine Learning Engineer: Google Cloud
- Microsoft Azure Machine Learning: Microsoft
- Deploying and Debugging ML Microservices: Coursera
