Results for "machine+learning+pipelines"
Multiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing
Duke 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
Skills you'll gain: PyTorch (Machine Learning Library), Model Evaluation, Model Deployment, MLOps (Machine Learning Operations), AI Workflows, Tensorflow, Dataflow, Performance Tuning, Deep Learning, Dashboard, Data Pipelines, Grafana, Artificial Neural Networks, Data Processing, Resource Utilization, Performance Analysis, Performance Metric, Data Manipulation
Skills you'll gain: Data Preprocessing, Data Cleansing, Data Pipelines, Feature Engineering, Data Quality, MLOps (Machine Learning Operations), Extract, Transform, Load, Data Transformation, Dataflow, Data Integrity, Apache Airflow, Data Validation, Version Control, Package and Software Management, Git (Version Control System), Quality Assurance, Exploratory Data Analysis, Cost Management, Resource Utilization, Virtual Environment
Skills you'll gain: Data Preprocessing, Model Evaluation, Hugging Face, Data Transformation, Feature Engineering, Data Pipelines, Image Analysis, Transfer Learning, Artificial Intelligence and Machine Learning (AI/ML), Natural Language Processing, Machine Learning Methods, Data Architecture, Machine Learning Software, Computer Vision, Digital Signal Processing, Artificial Neural Networks, Machine Learning Algorithms
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
What brings you to Coursera today?
Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Applied Machine Learning, Predictive Modeling, Feature Engineering, Workflow Management, Verification And Validation, Business Logic, Machine Learning, Supervised Learning, Statistical Machine Learning, Statistical Modeling, Performance Tuning, Machine Learning Algorithms, Scikit Learn (Machine Learning Library), Benchmarking, Random Forest Algorithm, Performance Analysis, Cost Management, Resource Utilization
Skills you'll gain: Data Flow Diagrams (DFDs), Apache Airflow, Data Pipelines, Data Modeling, Data Integration, Data Architecture, Data Warehousing, Apache Spark, Extract, Transform, Load, Data Processing, Data Transformation, Data Quality, Data Validation, Enterprise Security
University of Pennsylvania
Skills you'll gain: Statistical Machine Learning, Data Preprocessing, Model Evaluation, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Logistic Regression, Deep Learning, Probability Distribution, Supervised Learning, Statistics, Machine Learning Methods, Machine Learning, Agentic systems, Artificial Intelligence, Artificial Neural Networks, Algorithms, Python Programming
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: Model Evaluation, Model Deployment, Data Preprocessing, MLOps (Machine Learning Operations), Data Cleansing, Microservices, Data Pipelines, Feature Engineering, Data Quality, Data Validation, Containerization, Application Deployment, Extract, Transform, Load, Data Transformation, System Monitoring, Debugging, Applied Machine Learning, Machine Learning Methods, Performance Tuning, Machine Learning Algorithms
Google Cloud
Skills you'll gain: Feature Engineering, Generative AI, Model Deployment, Tensorflow, Google Cloud Platform, Keras (Neural Network Library), Machine Learning, Data Preprocessing, MLOps (Machine Learning Operations), Model Evaluation, Applied Machine Learning, Data Cleansing, Data Quality, AI Enablement, Prompt Engineering, Cloud Deployment, Supervised Learning, Scikit Learn (Machine Learning Library), AI Workflows, Cloud Computing
In summary, here are 10 of our most popular machine+learning+pipelines courses
- Machine Learning: DeepLearning.AI
- MLOps | Machine Learning Operations: Duke University
- Optimizing AI Workflows and Deploying Edge Models: Coursera
- Data Engineering & Pipeline Reliability for Machine Learning: Coursera
- Preparing Multimodal Data: Vision, Audio, and NLP Pipelines: Coursera
- Deploy ML Models to Production: KodeKloud
- Building, Optimizing, and Validating Machine Learning Models: Coursera
- Building Automated Data Pipelines with Spark,dbt,and Airflow: Coursera
- AI and Machine Learning Essentials with Python: University of Pennsylvania
- AI Agents and MLOps for Production-Ready AI: Packt
