MLOps-Kurse können Ihnen helfen zu verstehen, wie Modelle bereitgestellt, überwacht und skaliert werden. Sie können Fähigkeiten in Automatisierung, Pipeline-Aufbau, Modelltracking und Infrastruktur aufbauen. Viele Kurse stellen Werkzeuge und Workflows vor, die den úbergang von Modellen in produktive Umgebungen unterstützen.

Kompetenzen, die Sie erwerben: Google Cloud Platform, Model Deployment, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Unstructured Data, Big Data, MLOps (Machine Learning Operations), Applied Machine Learning, Model Training, Deep Learning, Data Pipelines, Machine Learning, Jupyter, Artificial Intelligence, Prototyping
★ 4.7 (47) · Mittel · Kurs · 1–3 Monate

Kompetenzen, die Sie erwerben: Model Training, Model Deployment, Exploratory Data Analysis, Data Engineering, Model Evaluation, Cloud Deployment, Data Preprocessing, Data Analysis, Data Wrangling, Model Optimization, Amazon Redshift, Machine Learning Software, Amazon Elastic Compute Cloud, Amazon CloudWatch, Application Deployment, AWS Kinesis, Data Pipelines, Extract, Transform, Load
Mittel · Kurs · 1–4 Wochen

Coursera
Kompetenzen, die Sie erwerben: Model Deployment, Fine-tuning, PyTorch (Machine Learning Library), Model Evaluation, Model Training, Vision Transformer (ViT), Model Optimization, Transfer Learning, MLOps (Machine Learning Operations), Natural Language Processing, Debugging, Containerization, Kubernetes, Docker (Software), Distributed Computing, Performance Tuning, Tensorflow, Deep Learning, Cloud Computing, Data Pipelines
Fortgeschritten · Spezialisierung · 1–3 Monate

Starweaver
Kompetenzen, die Sie erwerben: Prompt Engineering, Fine-tuning, Generative AI Agents, Retrieval-Augmented Generation, CrewAI, AI Orchestration, Prompt Engineering Tools, AI Enablement, Vector Databases, Agentic Workflows, AI Workflows, Model Deployment, AI Personalization, Generative AI, Transfer Learning, Agentic systems, MLOps (Machine Learning Operations), Python Programming, System Monitoring, Engineering
Mittel · Spezialisierung · 3–6 Monate

Kompetenzen, die Sie erwerben: Microsoft Azure, MLOps (Machine Learning Operations), Data Science, Machine Learning, Prompt Engineering Tools, Model Evaluation, Applied Machine Learning, Data Store, AI Workflows, Apache Spark, Data Strategy, Data Import/Export, Azure Synapse Analytics, Cloud Computing, Fine-tuning, Data Pipelines, Continuous Monitoring, Data Preprocessing, Scalability, Development Environment
Mittel · Spezialisierung · 1–3 Monate

Kompetenzen, die Sie erwerben: Retrieval-Augmented Generation, Model Deployment, LLM Application, LangChain, Large Language Modeling, Microservices, Test Driven Development (TDD), Software Architecture, Scalability, MLOps (Machine Learning Operations), Cloud Deployment, Cloud Computing Architecture, API Design, Site Reliability Engineering, Kubernetes, Prompt Engineering, Containerization, Infrastructure as Code (IaC), Python Programming, Performance Analysis
Mittel · Spezialisierung · 1–3 Monate

Kompetenzen, die Sie erwerben: Responsible AI, Model Deployment, Feature Engineering, MLOps (Machine Learning Operations), Model Training, Model Evaluation, Data Ethics, PyTorch (Machine Learning Library), Model Optimization, Scikit Learn (Machine Learning Library), Data Preprocessing, Data Pipelines, Deep Learning, Software Documentation, Technical Documentation
Mittel · Kurs · 1–4 Wochen

Coursera
Kompetenzen, die Sie erwerben: MLOps (Machine Learning Operations), Data Pipelines, Model Evaluation, Systems Design, Transfer Learning, Data Preprocessing, Data Quality, Feature Engineering, Deep Learning, Python Programming, Data Validation, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Software Engineering, Debugging, Supervised Learning, Git (Version Control System), Performance Metric, Statistical Analysis
Mittel · Spezialisierung · 1–3 Monate

Kompetenzen, die Sie erwerben: MLOps (Machine Learning Operations), Data Processing, Model Deployment, Data Pipelines, Google Cloud Platform, Applied Machine Learning, Analytics, Database Development, Data Infrastructure, Data Architecture, Data Analysis, Security Controls, Machine Learning, Data Modeling, Cloud Security, Data Visualization, Interactive Data Visualization, Data Storage Technologies, Disaster Recovery
★ 4.7 (14) · Fortgeschritten · Kurs · 1–3 Monate

Kompetenzen, die Sie erwerben: Threat Modeling, Feature Engineering, Anomaly Detection, Data Visualization, Data Presentation, MLOps (Machine Learning Operations), Agentic Workflows, Interactive Data Visualization, AI Orchestration, AI Security, A/B Testing, Generative AI Agents, Threat Management, Model Optimization, Open Web Application Security Project (OWASP), Technical Communication, Agentic systems, Continuous Monitoring, CI/CD, Reinforcement Learning
Mittel · Berufsbezogenes Zertifikat · 3–6 Monate

Kompetenzen, die Sie erwerben: Methoden des maschinellen Lernens, Generative AI-Agenten, Generative Modellarchitekturen, Künstliche Intelligenz, Prompt Engineering Tools, Generative KI, Maschinelles Lernen, Abruf-erweiterte Erzeugung, AI-Arbeitsabläufe, Verantwortungsvolle AI, MLOps (Operationen für maschinelles Lernen), Multimodale Aufforderungen, Amazon Webdienste, Amazon Web Services, Prompt-Muster, AI-Sicherheit, Amazonas-Felsen, Modellierung großer Sprachen, Künstliche Intelligenz und maschinelles Lernen (AI/ML), Schnelles Engineering, AWS SageMaker
★ 4.3 (16) · Anfänger · Kurs · 1–3 Monate

Microsoft
Kompetenzen, die Sie erwerben: Generative AI, Generative Model Architectures, MLOps (Machine Learning Operations), Generative Adversarial Networks (GANs), Model Deployment, Model Evaluation, Microsoft Azure, Model Training, PyTorch (Machine Learning Library), Deep Learning, Time Series Analysis and Forecasting, Tensorflow, Image Analysis, Forecasting, Prototyping
Mittel · Kurs · 1–4 Wochen