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: Daten-Pipelines, OpenAI, Semantisches Web, Verarbeitung natürlicher Sprache, Datenwissenschaft, AI-Arbeitsabläufe, Maschinelles Lernen, Künstliche Intelligenz, Tiefes Lernen, Skalierbarkeit, Generative KI
Fortgeschritten · Kurs · 1–3 Monate

Kompetenzen, die Sie erwerben: AI Security, Threat Modeling, Security Engineering, Security Testing, IT Security Architecture, Security Architecture Review, Hardening, Continuous Monitoring, Security Controls, Security Requirements Analysis, Security Strategy, Model Training, Vulnerability Assessments, Data Integrity, Data Validation, Model Evaluation, Information Privacy, Generative Adversarial Networks (GANs), Analysis, Design
Mittel · Kurs · 1–4 Wochen

Kompetenzen, die Sie erwerben: Kubernetes, Infrastructure as Code (IaC), Application Performance Management, Terraform, Identity and Access Management, Generative AI Agents, Metadata Management, Google Cloud Platform, Cloud Computing Architecture, Data Sharing, Data Pipelines, Cloud-Native Computing, Cloud Development, Prompt Engineering, Serverless Computing, Cloud Infrastructure, Generative AI, Cloud Security, Dashboard Creation, MLOps (Machine Learning Operations)
Fortgeschritten · Spezialisierung · 3–6 Monate

Google Cloud
Kompetenzen, die Sie erwerben: Feature Engineering, Model Optimization, Generative AI Agents, Model Deployment, Tensorflow, Google Cloud Platform, Model Training, Keras (Neural Network Library), Machine Learning, Data Preprocessing, Prompt Engineering, Machine Learning Software, Machine Learning Methods, MLOps (Machine Learning Operations), Generative AI, Model Evaluation, Cloud Infrastructure, Prompt Engineering Tools, Data Cleansing, Cloud Computing
Mittel · Spezialisierung · 3–6 Monate

Kompetenzen, die Sie erwerben: Supervised Learning, Model Optimization, PyTorch (Machine Learning Library), Fine-tuning, Generative Model Architectures, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Generative AI, Deep Learning, Model Training, Applied Machine Learning, Statistical Machine Learning, Classification And Regression Tree (CART), Autoencoders, Machine Learning Methods, Machine Learning Software, Machine Learning, MLOps (Machine Learning Operations), Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML)
Mittel · Spezialisierung · 3–6 Monate

Board Infinity
Kompetenzen, die Sie erwerben: MLOps (Machine Learning Operations), Model Deployment, Real Time Data, Containerization, Docker (Software), CI/CD, Model Training, Applied Machine Learning, Feature Engineering, Model Evaluation, Cloud Deployment, Model Optimization, Predictive Modeling, Web Scraping, Data Pipelines, Time Series Analysis and Forecasting, Exploratory Data Analysis, Spatial Data Analysis, Machine Learning, Continuous Monitoring
Mittel · Kurs · 1–4 Wochen

Kompetenzen, die Sie erwerben: Feature Engineering, Databricks, Data Engineering, PySpark, Data Lakes, Apache Airflow, Apache Spark, Data Pipelines, MLOps (Machine Learning Operations), Data Architecture, Data Processing, Artificial Intelligence and Machine Learning (AI/ML), Data Management, Data Storage, Python Programming, Artificial Intelligence, Machine Learning, SQL, Machine Learning Algorithms, Warehouse Management
Anfänger · Spezialisierung · 1–3 Monate

Kompetenzen, die Sie erwerben: PySpark, Data Lakes, Databricks, Data Pipelines, Apache Spark, Data Architecture, Data Transformation, Data Infrastructure, MLOps (Machine Learning Operations), Extract, Transform, Load, Data Processing, Data Manipulation, Data Cleansing, Data Validation, Data Maintenance, Data Management, Python Programming, Data Entry, SQL, Data Collection
Mittel · Kurs · 1–4 Wochen

Kompetenzen, die Sie erwerben: Feature Engineering, MLOps (Machine Learning Operations), Model Optimization, Google Cloud Platform, Generative AI Agents, Model Deployment, Tensorflow, Model Training, Dataflow, Big Data, Keras (Neural Network Library), Machine Learning, Data Preprocessing, Prompt Engineering, Machine Learning Software, CI/CD, Machine Learning Methods, Generative AI, Model Evaluation, Cloud Computing
Mittel · Berufsbezogenes Zertifikat · 3–6 Monate

Kompetenzen, die Sie erwerben: Dashboard Creation, Model Deployment, Feature Engineering, PySpark, Data Import/Export, Big Data, Apache Spark, Data Governance, Apache Hadoop, Dashboard, Apache Kafka, Data Store, Cloud Services, Cloud Deployment, Data Access, Cloud API, Data Architecture, Data Quality, Data Cleansing, Machine Learning Methods
Mittel · Spezialisierung · 3–6 Monate

Duke University
Kompetenzen, die Sie erwerben: Projektleitung, Produktdesign, Produktmanagement, Unüberwachtes Lernen, Klassifizierungs- und Regressionsbaum (CART), Qualität der Daten, MLOps (Operationen für maschinelles Lernen), Datenwissenschaft, Design erleben, Maschinelles Lernen, Modellevaluation, Bewertung des Modells, Modell-Einsatz, Tiefes Lernen, Datenqualität, Menschenzentriertes Design, Datenverwaltung, Modell Ausbildung, Daten-Ethik, Datenmanagement, Methoden des maschinellen Lernens, Benutzerfreundliches Design, Verantwortungsvolle AI
Anfänger · Spezialisierung · 3–6 Monate

Kompetenzen, die Sie erwerben: Feature Engineering, Apache Airflow, Databricks, MLOps (Machine Learning Operations), Data Pipelines, AI Orchestration, Data Lakes, Model Training, Apache Spark, Data Store, AI Workflows, Data Processing, Artificial Intelligence and Machine Learning (AI/ML), Data Transformation, Machine Learning, Data Collection, SQL, Data Storage, Machine Learning Algorithms, Warehouse Management
Fortgeschritten · Kurs · 1–4 Wochen